Table of contents

This volume contains the proceedings of the 11th International Conference on Damage Assessment of Structures (DAMAS) 2015. DAMAS has a long history of almost 20 years. The first DAMAS conference took place in 1995 (Pescara, Italy), followed by a biannual meeting in 1997 (Sheffield, UK), 1999 (Dublin, Ireland), 2001 (Cardiff, UK), 2003 (Southampton, UK), 2005 (Gdansk, Poland), 2007 (Torino, Italy), 2009 (Beijing, China), 2011 (Oxford, UK) and 2013 (Dublin, Ireland). The eleventh edition of DAMAS conference series, DAMAS 2015, is hosted by Ghent University, Belgium, and is held at the congress center Het Pand in Ghent city. Ghent is the capital and the largest city of the East Flanders province of the Flemish region of Belgium. Het Pand is the culture and congress center of Ghent University and is a historical monument.

The conference is established as a major international forum for research topics relevant to damage assessment of engineering structures and systems including numerical simulations, signal processing of sensor measurements and theoretical techniques as well as experimental case studies. The presentations of DAMAS 2015 are divided into 6 main sessions, namely 1) Structural Health and Condition Monitoring, 2) Damage in Civil Engineering, 3) Damage in Machineries, 4) Damage in Composite Materials, 5) Sensing and Sensors and 6) Signal Processing.

The organising committee is grateful to keynote speakers; Professor Guido De Roeck, Head of Structural Mechanics Division, KULeuven, Belgium, for his keynote lecture entitled 'Structural Health Monitoring: highlights and challenges', Professor Weidong Zhu, Department of Mechanical Engineering, University of Maryland, USA, for his keynote lecture entitled 'Vibration-based Structural Damage Detection: Theory and Applications' and Professor Wieslaw Ostachowicz, Head of the Laboratory of Active Materials and Smart Structures, Polish Academy of Sciences, Poland, for his keynote lecture entitled 'Damage Assessment and Reliability in Offshore Wind Turbines Technology'.

Special thanks go to members of the Scientific Committee of DAMAS 2015 for reviewing the articles published in this volume and for judging their scientific merits. Based on the comments of reviewers and the scientific merits of the submitted manuscripts, the articles were accepted for publication in the conference proceedings and for presentation at the conference venue. The accepted papers are of a very high scientific quality and contribute to advancement of knowledge in all research topics relevant to DAMAS conference.

The organising committee would like to thank prestigious research groups, who made a great contribution to DAMAS 2015: the group of Professor Lars Damkilde, Aalborg University, Denmark; the group of professor Gilbert-Rainer Gillich, Eftimie Murgu University of resita, Romania, the group of Professor Wieslaw Ostachowicz, Polish Academy of Sciences, Poland and the group of Dr Vikram Pakrashi, University College Cork, Ireland. Special thanks go to Dr Vikram Pakrashi for organizing the mini-symposium 'Damage Detection, System Identification and Health Monitoring for Offshore Wind and Wave Energy Devices'.

Finally, the organising committee would like to thank all authors, who have contributed to this volume and presented their research work at DAMAS 2015.

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the proceedings Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

The investigations of cracks growth in the fractured turbine rotors point out at theirs fatigue nature. The main reason of turbine shafts fatigue damage is theirs periodical startups which are typical for steam turbines. Each startup of a turbine is accompanied by the connection of turbine generator to electrical network. During the connection because of the phase shift between the vector of electromotive force of turbine generator and the vector of supply-line voltage the short-term but powerful reactive shaft torque arises. This torque causes torsional vibrations and fatigue damage of turbine shafts of different intensity. Based on the 3D finite element model of turbine shaft of the steam turbine K-200-130 and the mechanical properties of rotor steel there was estimated the fatigue damage of the shaft at its torsional vibrations arising as a result of connection of turbine generator to electric network.

Damage detection and estimation in structures using incomplete modal data is presented. In the proposed approach, damage location and severity is determined by solving an optimization problem using the constrained nonlinear multivariable function of Matlab (so- called fmincon) to perform constrained minimization. The feasibility of the presented method is validated with a three-story plane frame as numerical example containing one or several damages with different value of damage severity. The obtained results indicated that proposed method is effective and robust in detection and estimation of damage.

The stochastic dynamic damage location vector (SDDLV) method utilizes the vectors from the kernel of a damaged-induced transfer function matrix change to localize damages in a structure. The kernel vectors associated with the lowest singular values are converted into static pseudo-loads and applied alternately to an undamaged reference model with known stiffness matrix, hereby, theoretically, yielding characteristic stress resultants approaching zero in the damaged elements. At present, the discrimination between potentially damaged elements and undamaged ones is typically conducted on the basis of modified characteristic stress resultants, which are compared to a pre-defined tolerance value, without any thorough statistical evaluation. In the present paper, it is tested whether three widely-used statistical pattern-recognition-based damage-detection methods can provide an effective statistical evaluation of the characteristic stress resultants, hence facilitating general discrimination between damaged and undamaged elements. The three detection methods in question enable outlier analysis on the basis of, respectively, Euclidian distance, Hotelling's T² statistics, and Mahalanobis distance. The study of the applicability of these methods is based on experimentally obtained accelerations of a cantilevered residential-sized wind turbine blade subjected to an unmeasured multi-impulse load. The characteristic stress resultants are derived by applying the static pseudo-loads to a representative finite element (FE) model of the actual blade.

Vibration signal and its derivative have shown some promise in structural damage detection in previous research. However, the theoretical and practical difficulties of multi-damage detection in plate structures based on dynamic responses remain. In this paper, an efficient damage localization index based on frequency response function (FRF) is presented. The imaginary part of FRF (IFRF) is extracted to derive the new localization index due to its relation to modal flexibility. For avoiding the finite element model error, two-dimensional gapped smoothing method (GSM) is employed without the need for baseline data from a presumably undamaged structure. Experimental studies on a steel plate with two localized defects in different boundary conditions are performed. The results are compared with some typical damage indices in the literature, such as mode shapes, uniform load surface and IFRF. In order to mitigate the inherent disadvantages of GSM in anti-noise ability, a simple statistical treatment based on Thompson outlier analysis is finally used for noise suppression. The effect of damage level and boundary condition on the detection results is also investigated.

The presence of corrosion influences the dynamic behaviour of plates, by modifying its natural frequencies and mode shapes. Many methods to assess damages in structural elements are known, but they mainly address to the geometric discontinuities, where mass loss is insignificant. In some of the prior research, we have got success in achieving a mathematical relation between damage geometry and frequency shifts. Since the mass decrease is also associated with numerous corrosion mechanisms, the idea of this paper is to establish the influence of mass changes in the natural frequencies of plates and including this information in a baseline, to apply it in processes for corrosion assessment. Thus, by research the evaluation of frequency changes due to mass loss and stiffness decrease has been followed. The finite element analysis was performed, considering corroded area as being simulated by a constantly decreasing plate thickness. In this way, is highlighted the correlation between frequency changes in the transversal vibration modes and mass loss. The dependency between mass loss and frequencies is accomplished, as a mathematical relation as well. This relation is associated with another relation, who predicts the frequency decreases due to stiffness reduction, in order to find the curves of frequency shifts and promote them as a baseline for corrosion assessment. Also, a corrosion assessment method, based on the contrived frequency shift curves, has been developed and proved as reliable and easily applicable.

Structural Health Monitoring (SHM) faces several challenges before large-scale industrial application. First of all damage diagnosis has to be reliable. Therefore, common SHM approaches use highly advanced sensor techniques to monitor the whole structure on all possible failures. This results in an enormous amount of data gathered during service. The general effort can be drastically reduced, if the knowledge achieved during the sizing process is used. During sizing, potential failure modes and critical locations, so called hot spots, are already evaluated. A very sensitive SHM system can be developed, when the monitoring effort shifts from the damage to its impact on the structural behaviour and the so called damage indicators. These are the two main components of the SmartSHM approach, which reduces the monitoring effort significantly. Not only the amount of data is minimized, but also reliability and robustness are ensured by the SmartSHM approach.

This contribution demonstrates the SmartSHM approach by a cracked four point bending beam. To show general applicability a parametric study considering different profiles (bar, box, I, C, T, L, Z), crack positions and lengths has been performed. Questions of sensitivity and minimum size of the sensor network are discussed based on the results of the parametric study.

It has long been recognized that woodpecker is an excellent anti-shock organism, as its head and brain can bear high deceleration up to 1500 g under fast pecking. To investigate the mechanism of brain protection of woodpecker, we built a finite element model of a whole woodpecker using computed topography scanning technique and geometry modeling. Numerical results show that the periodical changing Young's modulus around the skull affects the stress wave propagation in head and makes the stress lowest at the position of the brain. Modal analysis reveals the application of pre-tension force to the hyoid bone can increase the natural frequency of woodpecker's head. The large gap between the natural and working frequencies enable the woodpecker to effectively protect its brain from the resonance injury. Energy analyses indicate the majority of the impact energy (99.7%) is stored in the bulk of body and is utilized in the next pecking. There is only a small fraction of it enters into the head (0.3%). The whole body of the woodpecker gets involved in the energy conversion and forms an efficient anti-shock protection system for the brain.

A Generalized Functional Model Based Method for vibration-based damage precise localization on structures consisting of 1D, 2D, or 3D elements is introduced. The method generalizes previous versions applicable to structures consisting of 1D elements, thus allowing for 2D and 3D elements as well. It is based on scalar (single sensor) or vector (multiple sensor) Functional Models which - in the inspection phase - incorporate the mathematical form of the specific structural topology. Precise localization is then based on coordinate estimation within this model structure, and confidence bounds are also obtained. The effectiveness of the method is demonstrated through experiments on a 3D truss structure where damage corresponds to single bolt loosening. Both the scalar and vector versions of the method are shown to be effective even within a very limited, low frequency, bandwidth of 3-59 Hz. The improvement achieved through the use of multiple sensors is also demonstrated.

This study focuses on the problem of vibration-based damage detection for a population of like structures. Although nominally identical, like structures exhibit variability in their characteristics due to variability in the materials and manufacturing. This inevitably leads to variability in the dynamics, which may be so significant as to mask deviations due to damage. Damage detection via conventional vibration-based methods, using a common threshold in the decision making mechanism thus becomes highly challenging. The study presents a detailed assessment of a recently introduced Multiple Model (MM) based AutoRegressive (AR) model parameter method aiming at addressing this problem. The assessment is based on high numbers of experimental test/inspection cases using composite beams damaged via impact, as well as comparisons with the corresponding conventional (single model based) method. The results confirm significant improvement over the method's conventional counterpart. A sensitivity analysis additionally indicates that the method is relatively insensitive to the model order, but sensitive to the specific beams selected as baseline (training) ones; in fact their selection may lead to excellent results.

Structural health monitoring acquires structural information through numerous sensor measurements. Vibrational measurement data render the dynamic characteristics of structures to be extracted, in particular of the modal properties such as natural frequencies, damping, and mode shapes. The stochastic subspace system identification has been recognized as a power tool which can present a structure in the modal coordinates. To obtain qualitative identified data, this tool needs to spend computational expense on a large set of measurements. In study, a stochastic system identification framework is proposed to improve the efficiency and quality of the conventional stochastic subspace system identification. This framework includes 1) measured signal processing, 2) efficient space projection, 3) system order selection, and 4) modal property derivation. The measured signal processing employs the singular spectrum analysis algorithm to lower the noise components as well as to present a data set in a reduced dimension. The subspace is subsequently derived from the data set presented in a delayed coordinate. With the proposed order selection criteria, the number of structural modes is determined, resulting in the modal properties. This system identification framework is applied to a real-world bridge for exploring the feasibility in real-time applications. The results show that this improved system identification method significantly decreases computational time, while qualitative modal parameters are still attained.

This paper presents a methodology for the multi-objective (MO) shape optimization of plate structure under stress criteria, based on a mixed Finite Element Model (FEM) enhanced with a sub-structuring method. The optimization is performed with a classical Genetic Algorithm (GA) method based on Pareto-optimal solutions and considers thickness distributions parameters and antagonist objectives among them stress criteria. We implement a displacement-stress Dynamic Mixed FEM (DM-FEM) for plate structure vibrations analysis. Such a model gives a privileged access to the stress within the plate structure compared to primal classical FEM, and features a linear dependence to the thickness parameters. A sub-structuring reduction method is also computed in order to reduce the size of the mixed FEM and split the given structure into smaller ones with their own thickness parameters. Those methods combined enable a fast and stress-wise efficient structure analysis, and improve the performance of the repetitive GA. A few cases of minimizing the mass and the maximum Von Mises stress within a plate structure under a dynamic load put forward the relevance of our method with promising results. It is able to satisfy multiple damage criteria with different thickness distributions, and use a smaller FEM.

Nonlinear behavior can be important for the monitoring of the structural state of mechanical systems since it can be mistakenly classified as a damage in the systems. However, nonlinear tools are still not consolidated and need further research for applications in mechanical system. Discrete-time Volterra series is an interesting mathematical framework to deal with nonlinear dynamics. It is a clear generalization of the linear convolution for weakly nonlinear systems. In the present work two different damage indicators are proposed based on Volterra models by considering linear and nonlinear contributions of the total response. The goal is to evaluate these indicators using an experimental test rig where the damages are simulated and considering the nonlinear regime of motion. The main advantages and drawbacks of the proposed methodology are highlighted in the final remarks.

A novel damage localization method is proposed, which is based on a substructuring approach and makes use of Vector Auto-Regressive with eXogenous input (VARX) models. The substructuring approach aims to divide the monitored structure into several multi-DOF isolated substructures. Later, each individual substructure is modelled as a VARX model, and the health of each substructure is determined analyzing the variation of the VARX model. The method allows to detect whether the isolated substructure is damaged, and besides allows to locate and quantify the damage within the substructure. It is not necessary to have a theoretical model of the structure and only the measured displacement data is required to estimate the isolated substructure's VARX model. The proposed method is validated by simulations of a two-dimensional lattice structure.

One of the main challenges in damage detection techniques is sensitivity to damage. During the last years, a large number of papers have used wavelet analysis as a sensitive mathematical tool for identifying changes in mode shapes induced by damage. This paper analyzes the effect of adding a mass to the structure at different positions. Depending on the location and severity of damage, the presence of the mass affects the natural frequencies and mode shapes in a different way. The paper applies a damage detection methodology proposed by the authors, although it has been modified in order to consider the addition of the mas. This methodology is based on a wavelet analysis of the difference of mode shapes of a damaged and a reference state. The singular behavior of a normalized weighted addition of wavelet coefficients is used as an indicator of damage. The presence of damage is detected by combining all the information provided by mode shapes and natural frequencies for different positions of the roving mass. A continuous wavelet transform is used to detect the difference between the response of a healthy state and a damaged one. The paper shows the results obtained for a beam with different cracks. The paper analyzes the sensitivity to damage of the proposed methodology by considering some practical issues such as the size of the crack, the number of measuring points and the effect of experimental noise.

Pipe structure is vulnerable to many types of damage, such as flow-accelerated corrosion, crack, and in the case of multi-layers pipe, debonding damage. A versatile damage inspection system is needed, where it must be easily used for variety types of pipeline, must have the capability to detect many types of damage, as well as must be able to carry out inspection in the working condition of the pipe system. In this paper, we present the Ultrasonic Propagation Imager (UPI) that demonstrated to meet those demands. The UPI system consists of a high speed Q-switched laser, a high speed scanning mirror, a DAQ system, and a changeable sensing system depends on applications. Advanced signal processing using ultrasonic wavenumber imaging algorithm and energy mapping were applied for damage detection of the pipe structures.

Human bone tissue is characterized as a material with high brittleness. Due to this nature, visible signs of cracking are not easy to be detected before final failure. The main objective of this work is to investigate if the acoustic emission (AE) technique can offer valuable insight to the fracture process of human femur specimens as in other engineering materials characterization. This study describes the AE activity during fracture of whole femur bones under flexural load. Before fracture, broadband AE sensors were used in order to measure parameters like wave velocity dispersion and attenuation. Waveform parameters like the duration, rise time and average frequency, were also examined relatively to the propagation distance as a preparation for the AE monitoring during fracture. After the ultrasonic study, the samples were partly cast in concrete and fixed as cantilevers. A point load was applied on the femur head, which due to the test geometry resulted in a combination of two different patterns of fracture, bending and torsion. Two AE broadband sensors were placed in different points of the sample, one near the fixing end and the other near the femur head. Preliminary analysis shows that parameters like the number of acquired AE signals and their amplitude are well correlated with the load history. Furthermore, the parameters of rise time and frequency can differentiate the two fracture patterns. Additionally, AE allows the detection of the load at the onset of fracture from the micro-cracking events that occur at the early loading stages, allowing monitoring of the whole fracture process. Parameters that have been used extensively for monitoring and characterization of fracture modes of engineering materials seem to poses characterization power in the case of bone tissue monitoring as well.

This paper presents a comparative study of a novel SHM technique for damage isolation. The performance of the Neutral Axis (NA) tracking based damage detection strategy is compared to other popularly used vibration based damage detection methods viz. ECOMAC, Mode Shape Curvature Method and Strain Flexibility Index Method. The sensitivity of the novel method is compared under changing ambient temperature conditions and in the presence of measurement noise. Finite Element Analysis (FEA) of the DTU 10 MW Wind Turbine was conducted to compare the local damage identification capability of each method and the results are presented. Under the conditions examined, the proposed method was found to be robust to ambient condition changes and measurement noise. The damage identification in some is either at par with the methods mentioned in the literature or better under the investigated damage scenarios.

The analysis of historical structures in need of preservation and restoration interventions is a very complex task due to the large uncertainties in the characterization of structural properties and detailing in view of the structural response. Moreover, the predictive performance of numerical analyses and simulations depend on the availability of information about the constructional properties of the architectural complex, crack patterns and active degradation phenomena. In particular, local changes in material properties or damage due to past events (such as earthquakes) can affect individual structural elements. They can be hardly detected as a result of the maintenance interventions carried out over the centuries and the possibility to carry out limited or even no destructive investigations due to the historical relevance of the structure. Thus, non-destructive investigations play a fundamental role in the assessment of historical structures minimizing, at the same time, the invasiveness of interventions. The present paper deals with an explanatory case study concerning the structural investigations carried out in view of the seismic assessment of an Italian historical monument, the Carthusian monastery of Trisulti in Collepardo, erected in 1204 under Pope Innocenzo HI. The relevance of the case study is due to the application, in combination, of different NDT methods, such as sonic tests, and active and passive infrared thermography, in order to characterize relevant masonry elements. Moreover, an advanced system for the in-situ nondestructive vibration-based estimation of the tensile loads in ancient tie-rods is described and the main results obtained from its application for the characterization of the tie-rods of the cloister are presented.

Modal parameters are often used for the structural damage assessment in the dynamic field. Usually, the changes in the modal parameters between different states are assumed as measures of damage. The frequencies are easy to identify, but in some circumstances they are not sensitive to damage and moreover they are mainly a global measure. On the contrary, the mode shapes are more suited for damage localization, but they are generally hard to identify accurately. The energy dissipation, and hence the damping, increases with damage. This feature is stable and has a monotonic behaviour, therefore, damping can be confidently used as an alternative or complementary measure for damage assessment in spite of the accuracy of its identification. However, the damping by itself suffers of the same drawbacks as the frequencies. The joint use of damping and mode shapes is an effective procedure for the damage identification. In the real world the damping is of nonproportional type and the measured mode shapes are complex. It is assumed that an increase of damage causes a modification of non-proportional damping and a variation of the modal complexity. The extent of modal complexity between two different structural states can be used to identify the damage through appropriate indicators. A number of such indicators is introduced and discussed. The effectiveness and sensitivity of the damage indicators are tested on theoretical and pseudo-experimental data.

This paper presents an enhanced method that accurately identifies natural frequencies of structures, via an important improvement of spectral lines density. Spectral lines density increases due to the superposition of many spectra, each spectrum being accomplished by subtracting certain number of samples from the original signal and using the power spectral density analysis. The newly achieved overlapped-spectrum shows important additions to spectral line number and makes more accurately identification of frequencies in the peak position of relevant amplitudes. In this way, modal analysis becomes more reliable and efficient. Method application assumes small frequency changes and the advantage of establishing more precisely the position and dimension of damage. The analysis of all results explicitly indicates an important assessment in the evaluation of frequency. Considering relevant aspects, it can be appreciated that the approached method offers a new development way in the vibration-based damage detection, allowing de possibility to perform more accurate evaluation of frequencies and introducing new features into the domain.

Damage detection methods based on vibration analysis make use of the modal parameter changes. Natural frequencies are the features that can be acquired most simply and inexpensively. But this parameter is influenced by environmental conditions, e.g. temperature and operational loads as additional masses or axial loads induced by restraint displacements. The effect of these factors is not completely known, but in the numerous actual research it is considered that they affect negatively the damage assessment process. This is justified by the small frequency changes occurring due to damage, which can be masked by the frequency shifts due to external loads. The paper intends to clarify the effect of external loads on the natural frequencies of beams and truss elements, and to show in which manner the damage detection process is affected by these loads. The finite element analysis, performed on diverse structures for a large range of temperature values, has shown that the temperature itself has a very limited effect on the frequency changes. Thus, axial forces resulted due to obstructed displacements can influence more substantially the frequency changes. These facts are demonstrated by experimental and theoretical studies. Finally, we succeed to adapt a prior contrived relation providing the frequency changes due to damage in order to fit the case of known external loads. Whereas a new baseline for damage detection was found, considering the effect of temperature and external loads, this process can be performed without other complication.

This paper presents a methodology for detection and localization of faults by using state observers. State Observers can rebuild the states not measured or values from points of difficult access in the system. So faults can be detected in these points without the knowledge of its measures, and can be track by the reconstructions of their states. In this paper this methodology will be applied in a system which represents a simplified model of a vehicle. In this model the chassis of the car was represented by a flat plate, which was divided in finite elements of plate (plate of Kirchoff), in addition, was considered the car suspension (springs and dampers). A test rig was built and the developed methodology was used to detect and locate faults on this system. In analyses done, the idea is to use a system with a specific fault, and then use the state observers to locate it, checking on a quantitative variation of the parameter of the system which caused this crash. For the computational simulations the software MATLAB was used.

The aim of this Acoustic Emission (AE) based Structural Health Monitoring project is to enable accurate location of AE sources in pressurised engineering plant and to use AE source location data to establish defect locations for use within Integri-Tech^TM; a finite element based analysis, monitoring and fitness for service assessment system. Integri-Tech^TM is a windows based system which carries out combined analysis and assessment providing fatigue life and remnant life calculations and inspection priorities presenting the results in an accessible web portal format. The software uses finite element stress models created in the companion software Model Wizard. The AE monitoring system that has been developed can be used with an array of up to four AE broad band sensor channels with associated signal processing. Using a flexible approach in MATLAB, the authors have developed algorithms which were used for analysing the received AE signals to extract information about the nature and location of the source. The ability to carry out source location and possibly perform real time monitoring (detecting cracking as it occurs) is attractive feature of the AE system developed for this project. The time of arrival (TOA) data was used by Integri-Tech^TM software to calculate source location using its own built-in algorithm, and this was verified independently using a MATLAB approach.

This paper presents an optimum measurement for the dynamic responses of structures from the operation of integration to respective derivation of acceleration's data using free-scaled wavelet functions. For this purpose, the numerical approach of integration and derivation has been developed for displacement measurement or determination of the third-order derivative (known as quantity of the jerk) from acquired accelerations. A simple improved algorithm is developed in order to optimally measure the dynamic quantities particularly, using Chebyshev and Haar wavelet functions. It is deduced that, stable measurement of dynamic quantities is independently achieved from the structural materials through a satisfactory optimum algorithm; that is capable of online monitoring, while emphasizing on maximum accuracy of the measurement with less computational time.

The work contains results of experimental investigation of elastic wave propagation in a bolted single-lap joint. Tests were carried out for the excitation perpendicular to the connection plane. In experimental studies, PZT transducers were used for both excitation and registration of ultrasonic waves. The analyses took into account varying contact conditions between the elements of the connection depending on the value of the prestressing force. The influence of loosening/tightening of bolts on the energy dissipation was analysed. The experimental results proved the influence of bolt torque on quantitative characteristics of the signals. To improve the diagnostic possibilities only the initial parts of signals were analysed.

The inspection possibilities of ground anchors are limited to destructive test such as pull-out test. Guided wave propagation gives an opportunity to develop an inspection system dedicated to determine the condition of inspected element without violation of their integrity. In this paper the experimental study on wave propagation in laboratory models of ground anchors are presented. Experiments were conducted for different bonding lengths and different frequencies of excitation. Waves were generated by a piezoelectric actuator and the laser vibrometry technique was used to register velocity signals. For all tested anchors it was possible to identify the boundary between steel and concrete based on the registered reflections in wave propagation signals.

Safety and reliability of hydrocarbon transportation pipelines represent a critical aspect for the Oil an Gas industry. Pipeline failures caused by corrosion, external agents, among others, can develop leaks or even rupture, which can negatively impact on population, natural environment, infrastructure and economy. It is imperative to have accurate inspection tools traveling through the pipeline to diagnose the integrity. In this way, over the last few years, different techniques under the concept of structural health monitoring (SHM) have continuously been in development.

This work is based on a hybrid methodology that combines the Magnetic Flux Leakage (MFL) and Principal Components Analysis (PCA) approaches. The MFL technique induces a magnetic field in the pipeline's walls. The data are recorded by sensors measuring leakage magnetic field in segments with loss of metal, such as cracking, corrosion, among others. The data provide information of a pipeline with 15 years of operation approximately, which transports gas, has a diameter of 20 inches and a total length of 110 km (with several changes in the topography). On the other hand, PCA is a well-known technique that compresses the information and extracts the most relevant information facilitating the detection of damage in several structures. At this point, the goal of this work is to detect and localize critical loss of metal of a pipeline that are currently working.

Modal filtering has numerous applications in the analysis of object dynamics. One possible use of this technique, recently presented in the literature, is damage detection. The main idea behind it, is to compare system characteristics filtered with modal filter for damaged and undamaged state. If a structural change appears in the system the filter does not work perfectly and its output significantly differs from one obtained for the healthy structure. Method is based on the modal parameter variation due to damage but does not require the modal analysis for every diagnosis. Another advantages are: computational simplicity and robustness for ambient temperature changes. The method was extended in 2008 with the possibility of damage localization. The idea here was based on the fact that local damage disturbs mode shapes locally. Instead of one modal filter, set of local modal filters were identified and used for further processing. Area of the structure connected with the filter with the worst performance is suspected of containing the damage. The method was already presented and positively verified but only for the beam-like structures. In this paper, application for plate-like structures is shown.

Structural damage detection using time domain vibration responses has attracted more and more researchers in recent years because of its simplicity in calculation and no requirement of a finite element model. This paper proposes a new approach to locate the damage using the auto correlation function of vibration response signals under sinusoidal excitation from different measurement points of the structure, based on which a vector named Auto Correlation Function at Maximum Point Value Vector (AMV) is formulated. A sensitivity analysis of the normalized AMV with respect to the local stiffness shows that under several specific frequency excitations, the normalized AMV has a sharp change around the local stiffness change location, which means that even when the damage is very small, the normalized AMV is a good indicator for the damage. In order to locate the damage, a damage index is defined as the relative change of the normalized AMV before and after damage. Several example cases in stiffness reduction detection of a frame structure valid the results of the sensitivity analysis, demonstrate the efficiency of the normalized AMV in damage localization and the effect of the excitation frequency on its detectability.

The information of the external loads is of great interest in many fields of structural analysis, such as structural health monitoring (SHM) systems or assessment of damage after extreme events. However, in most cases it is not possible to measure the external forces directly, so they need to be reconstructed. Load reconstruction refers to the problem of estimating an input to a dynamic system when the system output and the impulse response functions are usually the knowns. Generally, this leads to a so called ill-posed inverse problem, which involves solving an underdetermined linear system of equations. For most practical applications it can be assumed that the applied loads are not arbitrarily distributed in time and space, at least some specific characteristics about the external excitation are known a priori. In this contribution this knowledge was used to develop a more suitable force reconstruction method, which allows identifying the time history and the force location simultaneously by employing significantly fewer sensors compared to other reconstruction approaches. The properties of the external force are used to transform the ill-posed problem into a sparse recovery task. The sparse solution is acquired by solving a minimization problem known as basis pursuit denoising (BPDN). The possibility of reconstructing loads based on noisy structural measurement signals will be demonstrated by considering two frequently occurring loading conditions: harmonic excitation and impact events, separately and combined. First a simulation study of a simple plate structure is carried out and thereafter an experimental investigation of a real beam is performed.

Damage assessment of cement-based geomaterials during loading was conducted in this work by using the through-transmission ultrasound. For this purpose a built up system of ultrasound consisting of 96 channels and the specific sensors allowing to measure at the same time three types of waves (a bulk wave and two shear waves) were used. The continuous measurements enable to assess the damage of material through the constructed image of ultrasonic velocity as well as the attenuation of each wave during loading. The difference tomography method using the differential arrival times or relative amplitudes with respect to the initial stage confirms its efficacy through this work. The results show that all three types of wave can be used to capture the progressive damage in material but the bulk wave seems to be more sensitive than the shear waves.

Modern measurement techniques are improving in capability to capture spatial displacement fields occurring in deformed structures with high precision and in a quasi-continuous manner. This in turn has made the use of vibration-based damage identification methods more effective and reliable for real applications. However, practical measurement and data processing issues still present barriers to the application of these methods in identifying several types of structural damage. This paper deals with spatial Continuous Wavelet Transform (CWT) damage identification methods in beam structures with the aim of addressing the following key questions: (i) can the cost of damage detection be reduced by down-sampling? (ii) what is the minimum number of sampling intervals required for optimal damage detection ? The first three free vibration modes of a cantilever and a simple supported beam with an edge open crack are numerically simulated. A thorough parametric study is carried out by taking into account the key parameters governing the problem, including level of noise, crack depth and location, mechanical and geometrical parameters of the beam. The results are employed to assess the optimal number of sampling intervals for effective damage detection.

This paper reports on the damage caused by milling Carbon Fibre Reinforced Composite (CFRP) with 2-flute 4 mm-diameter solid carbide end mills, coated with titanium aluminium nitride. The machining parameters considered in work are, rotation speed, feed rate and depth of cut. Experiments were designed based on Box-Behnken design and the experiments conducted on a Mikrotool DT-110 CNC micro machine. A laser tachometer was used to ascertain a rotational speed for conducting any machining trial. Optical microscopy examination reveals minimum delamination value of 4.05 mm at the spindle speed of 25,000 rpm, depth of cut of 50μm and feed rate of 3 mm/min and the maximum delamination value of 5.04 mm at the spindle speed of 35000 rpm, depth of cut of 150μm and feed rate of 9 mm/min A mathematical model relating the milling parameters and delamination has been established.

Damage detection of any structure becomes the main concern in a failure analysis. Early failure detection is very important as it can prevent any catastrophic failure by replacing or repairing the damage part at early stage. One of the non-destructive methods of damage detection is using frequency based vibration analysis. Identification and comparison of a set of natural frequencies before and after damage is the main concern of this research. A rectangular plate clamped at all edges represented an initial undamaged structure. Based on Kachanov's definition, damage existence in a structure is introduced in the presence of some circular voids. The voids are generated randomly at different level of damage value. To obtain the Natural Frequencies, a Finite Element Model (FEM) of a clamped plate with the updated value of Young's Modulus is analyzed. From the FEM analysis result, it is found that the Natural Frequencies are shifted as the void existence increase. Using curve fitting, the model of Natural Frequency shifting as a function of damage evolution has been generated. It is found that the shifting of the Natural Frequency is greater at higher frequency value as indicated by the higher absolute gradient.

The detection techniques based on non-destructive testing (NDT) defects are preferable because of their low cost and operational aspects related to the use of the analyzed structure. In this study, we used the genetic algorithm (GA) for detecting and locating damage. The finite element was used for diagnostic beams. Different structures considered may incur damage to be modelled by a loss of rigidity supposed to represent a defect in the structure element. Identification of damage is formulated as an optimization problem using three objective functions (change of natural frequencies, Modal Assurance Criterion MAC and MAC natural frequency). The results show that the best objective function is based on the natural frequency and MAC while the method of the genetic algorithm present its efficiencies in indicating and quantifying multiple damage with great accuracy. Three defects have been created to enhance damage depending on the elements 2, 5 and 8 with a percentage allocation of 50% in the beam structure which has been discretized into 10 elements. Finally the defect with noise was introduced to test the stability of the method against uncertainty.

Beam-like structures are the most common components in real engineering, while single side damage is often encountered. In this study, a numerical analysis of single side damage in a free-free beam is analysed with three different finite element models; namely solid, shell and beam models for demonstrating their performance in simulating real structures. Similar to experiment, damage is introduced into one side of the beam, and natural frequencies are extracted from the simulations and compared with experimental and analytical results. Mode shapes are also analysed with modal assurance criterion. The results from simulations reveal a good performance of the three models in extracting natural frequencies, and solid model performs better than shell while shell model performs better than beam model under intact state. For damaged states, the natural frequencies captured from solid model show more sensitivity to damage severity than shell model and shell model performs similar to the beam model in distinguishing damage. The main contribution of this paper is to perform a comparison between three finite element models and experimental data as well as analytical solutions. The finite element results show a relatively well performance.

In this study, as one solution to the problem for condition assessment of existing short and medium span reinforced/prestressed concrete bridges, a new monitoring method using a public bus as part of a public transit system (bus monitoring system) is proposed, along with safety indices, namely, characteristic deflection, which is relatively free from the influence of dynamic disturbances due to such factors as the roughness of the road surface, and a structural anomaly parameter. A basic study was conducted by using the results of technical verification experiments and numerical analysis simulation. This paper describes the details of not only how to assess the bridge condition by public bus vibration measured in operating on Ube City bus network as a specific example for verify the system but also what kind of consideration we need to apply the system to existing bridges in overseas country.

In previous studies, a 1-D numerical predictive tool to simulate the salt induced corrosion of port assets in Australia has been developed into a 2-D and 3-D model based on current predictive probabilistic models. These studies use a probability distribution function based on the mean and standard deviation of the parameters for a structure incorporating surface chloride concentration, diffusion coefficient and cover. In this paper, this previous work is extended through an investigation of the distribution of actual cover by specified cover, element type and method of construction. Significant differences are found for the measured cover within structures, by method of construction, element type and specified cover. The data are not normally distributed and extreme values, usually low, are found in a number of locations. Elements cast insitu are less likely to meet the specified cover and the measured cover is more dispersed than those in elements which are precast. Individual probability distribution functions are available and are tested against the original function. Methods of combining results so that one distribution is available for a structure are formulated and evaluated. The ability to utilise the model for structures where no measurement have been taken is achieved by transposing results based on the specified cover.

Guided waves (GW) are finding more applications for structural health monitoring (SHM) of pipelines and other long, slender structures, particularly in the areas of corrosion and crack detection. Third party impact, both accidental and intentional, is also a major cause of pipeline failure. The use of low frequency (below 10 kHz) GW to detect damage caused by a third-party is investigated. Field test data on a 1 km long pipeline are compared with finite element (FE) predictions to illustrate the potential of low frequency GW to travel long distances along a pipeline. An FE study indicates the type and frequency of GW that can propagate long distances (low attenuation) without significant change in shape (low dispersion). The FE analysis is conducted on a typical 10 in (255 mm) diameter steel pipe with 7.8 mm wall thickness. The effects of pipe diameter and thickness on the GW propagation characteristics are illustrated. It is shown that certain frequencies for certain pipe geometries produce a very dispersive signal and should be avoided for GW SHM and the reasons for this are discussed.

Earthquake-induced pounding between adjacent buildings has been identified as one of the reasons for substantial damage or even total collapse of colliding structures. A major reason leading to interactions in buildings results from the differences in their dynamic parameters and also from insufficient distance between the structures. Although the research on structural pounding has been much advanced, the studies have mainly been conducted for concrete structures. The aim of this paper is to show the results of the non-linear numerical analysis focuses on damage due to pounding between two steel buildings under earthquake excitation. The numerical analysis has been performed using models of steel asymmetric structures with different number of storeys which makes them vibrate out-of-phase. Pounding between buildings has been controlled using three-dimensional gap-friction elements which become active when contact is detected. In order to identify the dynamic characteristics of analyzed structures, the modal analysis has been first conducted. Then, the detailed non-linear dynamic analysis of colliding structures has been performed. The acceleration time histories of the El Centro earthquake have been used in the numerical analysis. The results of the study clearly indicate that pounding may substantially influence the response of steel buildings intensifying their damage during earthquakes.

It is found that the hangers in many suspension bridges in China faced serious corrosion. The resistance capacities of the hangers decrease for corrosion, and the corroded hangers may break suddenly under tension forces. The sudden breakage of a hanger can induce violent vibrations and large changes of internal forces of the whole bridge. The safety of suspension bridges is endangered by corrosion of hangers. Using nonlinear dynamic analysis method and adopting 3D finite element model, the nonlinear dynamic responses of an actual suspension bridge to sudden breakage of a hanger are studied in this paper. The influences of sudden breakage of hanger on the bridge are analyzed in detail. Based on the analysis results, some useful suggestions about design and maintain of hangers are proposed.

Cementitious composites such as concrete pavements are susceptible to different damage modes, which are primarily caused by repeated loading and long-term deterioration. There is even greater concern that damage could worsen and occur more frequently with the use of heavier vehicles or new aircraft carrying greater payloads. Thus, the objective of this research is to engineer cementitious composites with capabilities of self-sensing or detecting damage. The approach was to enhance the damage sensitivity of cementitious composites by incorporating multi-walled carbon nanotubes (MWNT) as part of the mix design and during casting. However, as opposed to directly dispersing MWNTs in the cement matrix, which is the current state-of-art, MWNT-based thin films were airbrushed and coated onto sand particles. The film-coated sand was then used as part of the mix design for casting mortar specimens. Mortar specimens were subjected to compressive cyclic loading tests while their electrical properties were recorded simultaneously. The results showed that the electrical properties of these cementitious composites designed with film-coated sand exhibited extremely high strain sensitivities. The electrical response was also stable and consistent between specimens.

A numerical model of wheel-track system is developed for nucleation of squat-type fatigue cracks in rail material. The model is used for estimating the angles of squat cracks in three dimensions. Contact mechanics and multi-axial fatigue analysis are combined to study the crack initiation mechanism in rails. Nonlinear material properties, actual wheel-rail geometries and realistic loading conditions are considered in the modelling process. Using a 3D explicit finite element analysis the transient rolling contact behaviour of wheel on rail is simulated. Employing the critical plane concept, the material points with the largest possibility of crack initiation are determined; based on which, the 3D orientations/angles of the possible squat cracks are estimated. Numerical estimations are compared with sample results of experimental observations on a rail specimen with squat from the site. The findings suggest a proper agreement between results of modelling and experiment. It is observed that squat cracks initiate at an in-plane angle around 13°-22° relative to the rail surface. The initiation angle seen on surface plane is calculated around 29°-48°, while the crack tend to initiate in angles around 25°-31° in the rail cross-section.

Due to the random nature of the road excitation and the inherent uncertainties in bridge-vehicle system, damage identification of bridge structure through continuous monitoring under operating situation become a challenge problem. Methods for system identification and damage detection of a continuous two-span concrete bridge structure in time domain is presented using interaction forces from random moving vehicles as excitation. The signals recorded in different locations of the instrumented bridge are mixed with signals from different internal and external (road roughness) vibration sources. The damage structure is also modelled as the stiffness reduction in one of the beam element. For the purpose of system identification and damage detection three different output-only modal analysis techniques are proposed: The covariance-driven stochastic subspace identification (SSI-COV), the blind source separation algorithms (called Second Order Blind Identification) and the multivariate AR model. The advantages and disadvantages of the three algorithms are discussed. Finally, the null-space damage index, subspace damage indices and mode shape slope change are used to detect and locate the damage. The proposed approaches has been tested in simulation and proved to be effective for structural health monitoring.

The identification of damage in a bridge from changes in its vibrational behavior is an inverse problem of important practical value. Significant advances have been obtained on this topic in the last two-three decades, both from the theoretical and applied point of view. One of the main problems when dealing with the assessment of vibration based damage identification methods is the lack of experimental data recorded on real damaged structures. Due to this, a large number of damage identification algorithms are tested using data simulated by numerical models. The availability of data recorded on a damaged bridge before its demolition gave the authors the uncommon chance to verify the sensitivity and reliability of the IDDM basing on data recorded on a real structure. Specifically data recorded on a reinforced concrete single-span supported bridge in the Municipality of Dogna (Friuli, Italy) were used to apply the damage localization algorithm. Harmonically forced tests were conducted after imposing artificial, increasing levels of localized damage. In this paper the sensitivity of the method is discussed with respect to the number of instrumented locations and to the severity of the damage scenarios considered

There is now a common awareness that excessive strength is neither essential nor a synonymous of good performance in strong earthquakes. It is widely recognized that the design process should put more emphasis on predicting structural damage, according to the performance -based design philosophy. This paper presents an approach for assessing the damage level of lead rubber isolation devices and reinforced concrete piers, according to the performance-based design framework. The proposed performance limit states are based on the control of the materials strain, by means of the shear displacement of the bearing and the hinge rotation of the pier. The performance of the piers of different types of bridges is evaluated with the proposed methodology considering four different limit states.

The effect of prestress force magnitude on the dynamic properties of uncracked prestressed concrete structures is something that has been widely debated among researchers to date. The effect of pre- and post-tensioning force magnitude on the natural bending frequencies of cracked prestressed concrete structures is something that is more established, and widely agreed upon. This paper describes the results of dynamic impact testing on damaged post- tensioned concrete beams. The natural bending frequency of the cracked beams were determined through experimental modal analysis. Dynamic impact response signals were obtained at different levels of post-tensioning force for the cracked beams. The Fast Fourier Transform was implemented and a peak picking algorithm was subsequently used to determine the natural bending frequencies of the beams. The relationship between prestressing force and natural frequency for both the cracked and uncracked beam sections was determined. The results for the cracked beams were compared to the results for the same uncracked beam sections. A marked difference in vibration behaviour was observed for the cracked beams between the nonfully prestressed and the fully prestressed case. Conclusions from the study are drawn and have profound implications in the fields of system identification and structural health monitoring in pre- and post-tensioned concrete structures.

The bridge infrastructure in many countries of the world consists of medium span length structures built several decades ago and designed for very low seismic forces. Many of them are reinforced concrete structures that according to the current code regulations have to be rehabilitated to increase their seismic capacity. One way to reduce the vulnerability of the bridges is by using retrofitting techniques that increase the strength of the structure or by incorporating devices to reduce the seismic demand. One of the most common retrofit techniques of the bridges substructures is the use of RC jacketing; this research assesses the expected damages of seismically deficient medium length highway bridges retrofitted with reinforced concrete jacketing, by conducting a parametric study. We select a suite of twenty accelerograms of subduction earthquakes recorded close to the Pacific Coast in Mexico. The original structures consist of five 30 m span simple supported bridges with five pier heights of 5 m, 10 m, 15 m 20 and 25 m and the analyses include three different jacket thickness and three steel ratios. The bridges were subjected to the seismic records and non-linear time history analyses were carried out by using the OpenSEEs Plataform. Results allow selecting the reinforced concrete jacketing that better improves the expected seismic behavior of the bridge models.

Sea defence structures are expected to protect coasts for a long period, hence requiring reliable performance assessment strategies, in order to ensure their integrity and functionality. It has been demonstrated that rising sea level together with changing wave height can lead to increase risks of the failure to coastal defence structures. This paper presents a method for assessing the risk of wave overtopping failure, analysing the joint probability of sea water level and significant wave height under future hydraulic conditions due to climate change. Monte Carlo simulations are utilised to analyse the time-dependant overtopping failure probability of a seawall in the UK subjected to sea level rise. The numerical results for the flood defence example show that the seawall subjected to the sea level rise with high emission scenario could face to a significant increase of the frequency and the rate of overtopping discharge in comparison with the present date conditions without consideration of seawall crest settlement.

Structural performance deterioration of reinforced concrete structures has been extensively investigated, but very limited studies have been carried out to investigate the effect of reinforcement corrosion on time-dependent reliability with consideration of the influence of mechanical characteristics of the bond interface due to corrosion. This paper deals with how corrosion in reinforcement creates different types of defects in concrete structure and how they are responsible for the structural capacity deterioration of corrosion affected reinforced concrete structures during their service life. Cracking in cover concrete due to reinforcement corrosion is investigated by using rebar-concrete model and realistic concrete properties. The flexural strength deterioration is analytically predicted on the basis of bond strength evolution due to reinforcement corrosion, which is examined by the experimental data available. The time-dependent reliability analysis is undertaken to calculate the life time structural reliability of corrosion damaged concrete structures by stochastic deterioration modelling of reinforced concrete. The results from the numerical example show that the proposed approach is capable of evaluating the damage caused by reinforcement corrosion and also predicting the structural reliability of concrete structures during their lifecycle.

A large number of accidents, involving collapses of temporary grandstands during different types of events, were observed in the past. If the synchronized movement of people is tuned with the natural frequency of the affected part of the structure, resonance might occur. It may lead to severe damages of grandstands, their collapse or panic among the spectators. The aim of the paper is to assess, through preliminary experimental tests, the effectiveness of a polymer damper in damage reduction of a temporary steel grandstand. The damper considered in the study has been constructed out of two L-shape steel members bonded with polymer mass of high damping properties. The element has been installed as a diagonal one at the back part of the structure. The method has been compared with the typical solution of strengthening the grandstand with the diagonal stiffener of tubular cross section. The results of the study show that the responses of a temporary steel grandstand equipped with the polymer damper as well as with the typical stiffener are substantially different. The application of the polymer damper leads to the substantial increase in the level of structural damping ratio allowing to minimize the possibility of structural damage.

The failure prediction of simply supported annealed glass plates subjected to uniform loads is one of the main purposes in the design codes of the United States, Canada and the European Community. The methodologies and codes available in the literature are based on concepts and criteria applicable to the glass failure prediction; they evaluate the load associated to a specific probability of failure. The aim of this work is to estimate fragility curves for curtain glass under different uniform loads representative of the wind loads that they can be subjected, using the lifetime prediction model. The capacity of the structural elements was determined experimentally considering as-received annealed soda lime silica glass; this material is used in structural elements although the material is brittle and random. The capacity and demand are associated with the life time prediction model. The results let us understand the glass failure mechanisms of glass panels with different thickness, as well as assess their probability of failure by estimating fragility curves.

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalised cross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalisedcross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

Maintaining civil infrastructure, including bridges, has been a keen technical issue in developed countries and will surely be one in developing countries in the near future. An effective maintenance strategy strongly depends on timely decisions on the health condition of the structure. Bridge health monitoring (BHM) using vibration data is widely recognized to be one of the effective technologies that aid decision-making on bridge maintenance. This research focuses on long-term BHM expecting that changes in physical properties of the bridge subject to aged-deterioration progress slowly. In the practical application of the long-term BHM, one of the difficulties is that the observed vibration data includes environmental influences such as temperature change. In order to achieve high accuracy in evaluating modal parameters of the bridge, other influencing variables have to be taken into consideration. In this study, temperature is considered as the main environmental factor by means of a regression analysis. The Mahalanobis distance (MD), a multivariate statistical distance, is adopted to emphasize potential changes in the identified modal parameters. The validity of the proposed approach is investigated utilizing vibration data measured at a real bridge in service.

The offshore wind industry is rapidly maturing and is now expanding to more extreme environments in deeper water and farther from shore. To date fixed foundation types (i.e. monopoles, jackets) have been primarily used but become uneconomical in water depths greater than 50m. Floating foundations have more complex dynamics but at the moment no design has reached commercialization, although a number of devices are being tested at prototype stage. The development of concepts is carried out through physical model testing of scaled devices such that to better understand the dynamics of the system and validate numerical models. This paper investigates the testing of a scale model of a tension moored wind turbine at two different scales and in the presence and absence of a spring damper controlling its dynamic response. The models were tested under combined wave and wind thrust loading conditions. The analysis compares the motions of the platform at different scales and structural conditions through RAO, testing a mooring spring damper for load reductions.

With the importance of renewable energy well-established worldwide, and targets of such energy quantified in many cases, there exists a considerable interest in the assessment of wind and wave devices. While the individual components of these devices are often relatively well understood and the aspects of energy generation well researched, there seems to be a gap in the understanding of these devices as a whole and especially in the field of their dynamic responses under operational conditions. The mathematical modelling and estimation of their dynamic responses are more evolved but research directed towards testing of these devices still requires significant attention. Model-free indicators of the dynamic responses of these devices are important since it reflects the as-deployed behaviour of the devices when the exposure conditions are scaled reasonably correctly, along with the structural dimensions. This paper demonstrates how the Hurst exponent of the dynamic responses of a monopile exposed to different exposure conditions in an ocean wave basin can be used as a model-free indicator of various responses. The scaled model is exposed to Froude scaled waves and tested under different exposure conditions. The analysis and interpretation is carried out in a model-free and output-only environment, with only some preliminary ideas regarding the input of the system. The analysis indicates how the Hurst exponent can be an interesting descriptor to compare and contrast various scenarios of dynamic response conditions.

Tuned liquid column dampers have been proved to be successful in mitigating the dynamic responses of civil infrastructure. There have been some recent applications of this concept on wind turbines and this passive control system can help to mitigate responses of offshore floating platforms and wave devices. The control of dynamic responses of these devices is important for reducing loads on structural elements and facilitating operations and maintenance (O&M) activities. This paper outlines the use of a tuned single liquid column damper for the control of a tension leg platform supported wind turbine. Theoretical studies were carried out and a scaled model was tested in a wave basin to assess the performance of the damper. The tests on the model presented in this paper correspond to a platform with a very low natural frequency for surge, sway and yaw motions. For practical purposes, it was not possible to tune the liquid damper exactly to this frequency. The consequent approach taken and the efficiency of such approach are presented in this paper. Responses to waves of a single frequency are investigated along with responses obtained from wave spectra characterising typical sea states. The extent of control is quantified using peak and root mean squared dynamic responses respectively. The tests present some guidelines and challenges for testing scaled devices in relation to including response control mechanisms. Additionally, the results provide a basis for dictating future research on tuned liquid column damper based control on floating platforms.

Although aspects of power generation of many offshore renewable devices are well understood, their dynamic responses under high wind and wave conditions are still to be investigated to a great detail. Output only statistical markers are important for these offshore devices, since access to the device is limited and information about the exposure conditions and the true behaviour of the devices are generally partial, limited, and vague or even absent. The markers can summarise and characterise the behaviour of these devices from their dynamic response available as time series data. The behaviour may be linear or nonlinear and consequently a marker that can track the changes in structural situations can be quite important. These markers can then be helpful in assessing the current condition of the structure and can indicate possible intervention, monitoring or assessment. This paper considers a Delay Vector Variance based marker for changes in a tension leg platform tested in an ocean wave basin for structural changes brought about by single column dampers. The approach is based on dynamic outputs of the device alone and is based on the estimation of the nonlinearity of the output signal. The advantages of the selected marker and its response with changing structural properties are discussed. The marker is observed to be important for monitoring the as- deployed structural condition and is sensitive to changes in such conditions. Influence of exposure conditions of wave loading is also discussed in this study based only on experimental data.

The use of visual inspections as the primary data gathering tool for modern bridge management systems is widespread, and thus leads to the collection and storage of large amounts of data points. Consequently, there exists an opportunity to use multivariate techniques to analyse large scale data sets as a descriptive and predictive tool. One such technique for analysing large data sets is principal component analysis (PCA), which can reduce the dimensionality of a data set into its most important components, while retaining as much variation as possible. An example is applied to a network of bridges in order to demonstrate the utility of the technique as applied to bridge management systems.

An earthquake has three important characteristics; namely, amplitude, frequency content and duration. Amplitude and frequency content have a direct impact but not necessarily the sole cause of structural damage. Regarding the duration, some researchers show a high correlation between strong motion duration and structural damage whereas some others find no relation. This paper focuses on the ground motion durations characterized by Arias Intensity (AI). High duration may increase the damage state of structure for the damage accumulation. This paper investigates the response time histories (acceleration, velocity and displacement) of RC buildings under the different strong motion durations. Generally, eight earthquake records were selected from different soil type, and these records were grouped according to their PGA and frequency ranges. Maximum plastic rotation and drift response was chosen as damage indicator. In general, there was a positive correlation between strong motion duration and damage; however, in some PGA and frequency ranges input motions with shorter durations might cause more damage than the input motions with longer durations. In soft soils, input motions with longer durations caused more damage than the input motions with shorter durations.

Earthquakes have been affecting human's safety through human's history. Previous studies on earthquake, mostly, focused on the performance of buildings or evaluating damages. This paper, however, compares different factors that have influence on the damage of buildings with a case study in Wenchuan earthquake, using multiple linear regression methodology, so as to identify to what extend this factors influence the buildings' damages, then give the rank of importance of these factors. In this process, authors take the type of structure as a dummy variable to compare the degree of damages caused by different types of structure, which were barely studied before. Besides, Factor Analysis Methodology(FA) will be adapted to classify factors, the results of which will simplify later study. The outcome of this study would make a big difference in optimizing the seismic design and improving residential seismic quality.

A numerical imperfection study is carried out on a hot rolled tubular brace member under displacement controlled amplitudes. An appropriate range of global and local imperfections is used in the finite element analyses to evaluate the initial-post buckling compressive strength, lateral storey drift, energy dissipation and mid-length lateral deformation of the brace member. The purpose of this study is to assess the impact of the geometrical imperfection on the numerical performance, and to determine an amplitude range that can be used unequivocally for numerical modelling of brace members. It is shown that the amplitude of global imperfections has an effect on the initial response, whereas the amplitude of local imperfections has influence on the resistance capacity of the brace member at higher ductility level. Based on the results, a refined range of amplitude of global and local imperfections is proposed. This range is found to have a good agreement with design standards. In addition, an already established equation to find lateral deformation is compared to results from the analyses and found that the equation with some modification can be used accurately in design. In this paper, a modification factor is proposed in the equation to find the lateral deformation to account for the imperfection amplitude in the numerical analyses of brace members.

The passage of a vehicle over a bridge leaves a unique footprint in the form of measured strains (or displacements) across the structure. This paper proposes a new level I damage detection method for short-span bridges using footprints of Dynamic Amplification Factor (DAF) versus vehicle speed. The total response of a bridge to a moving load is time- varying, and it can be assumed to be made of two components: 'static' and 'dynamic'. Here, DAF is defined as the ratio of the maximum total response to the maximum 'static' component. For a given bridge, DAF patterns will vary with vehicle configuration. However, for a vehicle configuration (or a number of them), the mean DAF pattern measured on the bridge will remain unaltered unless the conditions of the bridge changed. The latter is the subject of investigation in this paper. In order to test the feasibility of using these patterns for monitoring purposes, damage is simulated within a bridge model as stiffness losses of 10% and 30% at mid-span. Changes in stiffness are identified by differences between DAF patterns corresponding to the healthy and damaged bridges. Results show to be more sensitive to damage than a traditional level I damage detection method based on variation of natural frequencies.

This paper includes an investigation for the deformations, including deflections and damage modes, which occur in reinforced concrete (RC) slabs when subjected to blast loads of explosions. The slab considered for the investigation is a one-way square RC slab with the dimensions of 1000 x 1000 x 40 mm, fixed supported at two opposite sides. It was subjected to close-in detonations of three different charge weights for a constant standoff distance. For the study, the slab was analysed using the numerical method by means of nonlinear finite element analysis. The slab was modelled as 3-D structural continuum using LS-DYNA software. For concrete modelling, two constitutive models were selected, namely the KCC and Winfrith concrete models. Blast loads were applied to the slab through the Lagrangian approach, and the blast command available in the software, namely LOAD_BLAST_ENHANCED, was selected for the application. The deflections and damage modes results obtained were compared to those from a previously published experiment. From the study, both the KCC and Winfrith concrete models effectively and satisfactorily estimated the actual slab maximum deflection. For damage modes, the KCC model appeared to be capable to capture satisfactorily the general damage mode including flexural cracks. However, the model could not capture the local shear mode at the middle of slab (spallation) because the Lagrangian approach does not simulate the interaction between the ambient air and the solid slab.

On March 8^th, 2010 Karakocan-Elazig earthquake of magnitude 6.0 occurred at a region where masonry and adobe construction is very common. Karakocan-Elazig is located in a high seismicity region on Eastern Anatolian Fault System (EAFS). Due to the earthquake, 42 people were killed and 14'113 buildings were damaged. Another city, Van located at South east of Turkey is hit by earthquakes with M = 7.2 occurred on October 23^rd, 2011 at 13:41 (local time), whose epicenter was about 16 km north of Van (Tabanli village) and M = 5.6 on November 9^th, 2011 with an epicenter near the town of Edremit, south of Van and caused the loss of life and heavy damages. Both earthquakes killed 644 people and 2608 people were injured. Approximately 10'000 buildings were seriously damaged. There are many traditional types of structures existing in the region hit by earthquakes (both Van and Elazig). These buildings were built as adobe, unreinforced masonry or mixed type. These types of buildings are very common in rural areas (especially south and east) of Turkey because of easy workmanship and cheap construction cost. Many of those traditional type structures experienced serious damages. The use of masonry is very common in some of the world's most hazard-prone regions, such as in Latin America, Africa, the Indian subcontinent and other parts of Asia, the Middle East, and southern Europe. Based on damage and failure mechanism of those buildings, the parameters affecting the seismic performance of those traditional buildings are analyzed in this paper. The foundation type, soil conditions, production method of the masonry blocks, construction method, the geometry of the masonry walls, workmanship quality, existence of wooden beams, type of roof, mortar between adobe blocks are studied in order to understand the reason of damage for these types of buildings.

Wind turbine support towers at heights in excess of 90m are nowadays being formed in steel, concrete and hybrid concrete and steel structures. As is the case for all towers of this height, the towers will be assembled using a number of segments, which will be connected in some way. These local connections are to be viewed as areas of potential local weakness in the overall tower assembly and require care in terms of design and construction. This work concentrates on identifying local damage which can occur at an interface connection by either material or bolt/tendon failure. Spatial strain patterns will be used to try to identify local damage areas around a 3 dimensional tower shell. A Finite Element (FE) model will be assembled which will describe a hybrid tower as a continuum of four-noded, two-dimensional Reisser- Mindlin shell elements. In order to simulate local damage, an element around the circumference of the tower interface will be subjected to a reduced stiffness. Strain patterns will be observed both in the undamaged and damaged states and these signals will be processed using a Discrete Wavelet Transform (DWT) algorithm to investigate if the damaged element can be identified.

The utilization of vibration signals for structural damage detection (SDD) is appealing due to the strong theoretical foundation of such approaches, ease of data acquisition and processing efficiency. Different methods are available for defining damage sensitive features (DSFs) based on vibrations, such as modal analysis or time series methods. The present paper proposes the use of partial autocorrelation coefficients of acceleration responses as DSFs. Principal component (PC) analysis is used to transform the initial DSFs to scores. The resulting scores from the healthy and damaged states are used to select the PCs which are most sensitive to damage. These are then used for making decisions about the structural state by means of statistical hypothesis testing conducted on the scores. The approach is applied to experiments with a laboratory scale wind turbine blade (WTB) made of glass-fibre reinforced epoxy composite. Damage is non-destructively simulated by attaching small masses and the WTB is excited with the help of an electrodynamic shaker using band-limited white noise. The SDD results for the selected subsets of PCs show a clear improvement of the detectability of early damages compared to other DSF selections.

The stochastic dynamic damage location vector (SDDLV) method has previously proved to facilitate effective damage localization in truss- and plate-like structures. The method is based on interrogating damage-induced changes in transfer function matrices in cases where these matrices cannot be derived explicitly due to unknown input. Instead, vectors from the kernel of the transfer function matrix change are utilized; vectors which are derived on the basis of the system and state-to-output mapping matrices from output-only state-space realizations. The idea is then to convert the kernel vectors associated with the lowest singular values into static pseudo-loads and apply these alternately to an undamaged reference model with known stiffness matrix. By doing so, the stresses in the potentially damaged elements will, theoretically, approach zero. The present paper demonstrates an application of the SDDLV method for localization of structural damages in a cantilevered residential-sized wind turbine blade. The blade was excited by an unmeasured multi-impulse load and the resulting dynamic response was captured through accelerometers mounted along the blade. The static pseudo-loads were applied to a finite element (FE) blade model, which was tuned against the modal parameters of the actual blade. In the experiments, an undamaged blade configuration was analysed along with different damage scenarios, hereby testing the applicability of the SDDLV method.

Many assessment and detection methods are used to diagnose faults in machines. High accuracy in fault detection and diagnosis can be achieved by using numerical methods with noise-resistant properties. However, to some extent, noise always exists in measured data on real machines, which affects the identification results, especially in the diagnosis of early- stage faults. In view of this situation, a damage assessment method based on blind source separation and dynamic fuzzy neural network (DFNN) is presented to diagnose the early-stage machinery faults in this paper. In the processing of measurement signals, blind source separation is adopted to reduce noise. Then sensitive features of these faults are obtained by extracting low dimensional manifold characteristics from the signals. The model for fault diagnosis is established based on DFNN. Furthermore, on-line computation is accelerated by means of compressed sensing. Numerical vibration signals of ball screw fault modes are processed on the model for mechanical fault diagnosis and the results are in good agreement with the actual condition even at the early stage of fault development. This detection method is very useful in practice and feasible for early-stage fault diagnosis.

The crankshaft output end is generally connected with generator rotor through the coupling in diesel generating set. When using rigid coupling, the attachments and connecting parts of generator rotor (especially at larger gyration radius) are vulnerable to fatigue damage even if the vibration level of the generating set does not exceed the acceptable "usual value". In order to investigate the reasons, the torsional vibration of the rotor in the diesel generating set was calculated and measured in this paper, which shows that using high rigidity coupling would result in large torsional vibration on the generator rotor, and that the linear vibration (the tangential vibration) value induced by torsional vibration at larger gyration radius of generator motor is almost the same as the vibration level of the generating set. Then, the vibration level of generating set was obtained, and the maximum vibration velocities of the generator are below the permissible value regulated by ISO 8528-9. But the velocities of synthetic vibration of the generating set vibration and the linear vibration induced by torsional vibration at larger gyration radius are much higher than permissible value 2(28mm/s) regulated by ISO 8528-9, which may be the reason of the mechanical damage of the attachments and connecting parts at larger gyration radius of generator motor caused by exceeded vibration.

This study presents an vibration-based system designed for structural health monitoring of wind turbine blades. Mechanical energy is introduced by means of an electromechanical actuator mounted inside the blade. The actuator's plunger periodically hits the blade structure; the induced vibrations propagate along the blade and are measured by an array of accelerometers. Unsupervised learning is applied to the data: the vibration patterns corresponding to the undamaged blade are used to create a statistical model of the reference state. During the detection stage, the current vibration pattern is compared with the reference state, and the novelties can be associated with damage. The vibration pattern is described by the covariance matrix between the accelerometer signals. The mid-range frequencies are used: this range is above the frequencies excited by blade-wind interaction, thus ensuring a good signal-to-noise ratio. Simultaneously, the frequencies are low enough to be able to propagate the entire blade length, so good results can be obtained even using only one actuator. The system is demonstrated on a real 34m blade mounted on a test rig. Using the suggested approach, the system enables detection of, e.g., a 20cm long trailing edge opening under realistic noise conditions. It is also demonstrated that the system provides rough information about damage location. Progression of damage, if any, can also be detected.

The problem of damage detection in an operating wind turbine under normal operating conditions is addressed. This is characterized by difficulties associated with the lack of measurable excitation(s), the vibration response non-stationary nature, and its dependence on various types of uncertainties. To overcome these difficulties a stochastic approach based on Random Coefficient (RC) Linear Parameter Varying (LPV) AutoRegressive (AR) models is postulated. These models may effectively represent the non-stationary random vibration response under healthy conditions and subsequently used for damage detection through hypothesis testing. The performance of the method for damage and fault detection in an operating wind turbine is subsequently assessed via Monte Carlo simulations using the FAST simulation package.

Acoustic Emission (AE) sensors were used to detect signals arising from a cylindrical roller bearing with artificial defects seeded onto the outer raceway. An SKF N204ECP roller bearing was placed between two double row spherical roller bearings, type SKF 22202E, and loaded between 0.29 and 1.79kN. Speed was constant at 5780rpm. High frequency analysis allowed insight into the condition of the bearings through the determination of an increase in the structural resonances of the system as the size of an artificial defect was increased. As higher loads were applied, frequencies around 100kHz were excited, indicating the release of AE possibly attributed to friction and the plastic deformation as peaks, induced through engraving of the raceway, were flattened and worn down. Sensitivity of AE to this level in bearings indicates the potential of the technique to detect the early stages of bearing failure during life tests.

This study assesses capacities of the global sensitivity analysis combined together with the kriging formalism to be useful in the robust stability analysis of brake systems, which is too costly when performed with the classical complex eigenvalues analysis (CEA) based on finite element models (FEMs). By considering a simplified brake system, the global sensitivity analysis is first shown very helpful for understanding the effects of design parameters on the brake system's stability. This is allowed by the so-called Sobol indices which discriminate design parameters with respect to their influence on the stability. Consequently, only uncertainty of influent parameters is taken into account in the following step, namely, the surrogate modelling based on kriging. The latter is then demonstrated to be an interesting alternative to FEMs since it allowed, with a lower cost, an accurate estimation of the system's proportions of instability corresponding to the influent parameters.

Disk-drum type rotors are widely used in industry for their high stiffness and low weight properties. In disk-drum type rotors, the adjacent disks and drums are commonly connected by bolted joints. Those rotating joint interfaces are subjected to numerous combinations of loads during normal operation, where loosening of the connecting bolts might occur. The bolt loosening will change the local stiffness of the rotor, which in turn affect the rotor dynamics and even result in structural failures. In this paper, the local stiffness of a disk- drum rotor with bolt loosening is investigated numerically. A three-dimensional (3D) finite element (FE) model for the bolted disk-drum joint is established in ANSYS, where the bolt loosening is simulated by reducing the preloads of certain bolts, and removing those bolts as the limiting case. Simulations are performed on the FE model to evaluate the joint behaviour under static loads. Periodic variations of the joint deflections with respect to the rotation angle of the shaft are obtained, which implies the appearance of the time-varying local stiffness in the rotor system. The studies in this paper help accurate prediction of the rotor dynamics and early detection of bolt loosening.

The paper presents selected aspects of modelling bonded joints of polymer composite materials by finite element method. The shear-loaded adhesive lap joints made of epoxy-graphite and epoxy-glass composite materials were investigated. The research objective was to determine correct modelling of adhesive layers using cohesive elements and of bonded joints for selected epoxy composite materials with different mechanical properties (e.g. Young's modulus) and geometrical dimensions, using, however, the same type of adhesive. The numerical analysis was performed based on experimental tests. A comparison is made between the distribution of reduced stress in the examined joint models according to the H-M- H hypothesis and that determined according to the maximum principal stress hypothesis. The finite elements analysis was performed in ABAQUS software and the traction-separation failure criterion was used for the damage onset and growth in the adhesive layer.

Lubrication oil plays a decisive role to maintain a reliable and efficient operation of gear transmissions. Many offline methods have been developed to monitor the quality of lubricating oils. This work focus on developing a novel online method to diagnose oil degradation based on the measurements from power supply system to the gearbox. Experimental studies based on an 10kW industrial gearbox fed by a sensorless variable speed drive (VSD) shows that measurable changes in both static power and dynamic behaviour are different with lube oils tested. Therefore, it is feasible to use the static power feature to indicate viscosity changes at low and moderate operating speeds. In the meantime, the dynamic feature can separate viscosity changes for all different tested cases.

This paper discusses the fault feature selection using principal component analysis (PCA) for bearing faults classification. Multiple features selected from the time-frequency domain parameters of vibration signals are analyzed. First, calculate the time domain statistical features, such as root mean square and kurtosis; meanwhile, by Fourier transformation and Hilbert transformation, the frequency statistical features are extracted from the frequency spectrum. Then the PCA is used to reduce the dimension of feature vectors drawn from raw vibration signals, which can improve real time performance and accuracy of the fault diagnosis. Finally, a fuzzy C-means (FCM) model is established to implement the diagnosis of rolling bearing faults. Practical rolling bearing experiment data is used to verify the effectiveness of the proposed method.

This paper presents an analysis to achieve the impact damage of the wing structure under real dynamic load. MPCCI tools are utilized to convert wing aerodynamic load into structural Finite Element Method (FEM) node load. The ANSYS/LS-DYNA code is also used to simulate the dynamic loading effects of the wing structure hit by several projectiles, including both active damage mechanism and common damage mechanism. In addition, structural node force on the leading edge and the midline is compared to the aerodynamic load separately. Furthermore, the statistical analysis of the penetrating size and the stress concentration around the damage holes indicates that under the same load situation, the structural damage efficiency of active damage mechanism is significantly higher than the one of common damage mechanism.

The real-time structural damage detection on large slender structures has one of its main application on offshore Horizontal Axis Wind Turbines (HAWT). The renewable energy market is continuously pushing the wind turbine sizes and performances. This is the reason why nowadays offshore wind turbines concepts are going toward a 10 MW reference wind turbine model. The aim of the work is to perform operational analyses on the 10-MW reference wind turbine finite element model using an aeroelastic code in order to obtain long-time-low- cost simulations. The aeroelastic code allows simulating the damages in several ways: by reducing the edgewise/flapwise blades stiffness, by adding lumped masses or considering a progressive mass addiction (i.e. ice on the blades). The damage detection is then performed by means of Operational Modal Analysis (OMA) techniques. Virtual accelerometers are placed in order to simulate real measurements and to estimate the modal parameters. The feasibility of a robust damage detection on the model has been performed on the HAWT model in parked conditions. The situation is much more complicated in case of operating wind turbines because the time periodicity of the structure need to be taken into account. Several algorithms have been implemented and tested in the simulation environment. They are needed in order to carry on a damage detection simulation campaign and develop a feasible real-time damage detection method. In addition to these algorithms, harmonic removal tools are needed in order to dispose of the harmonics due to the rotation.

This work provide a model based on machine learning techniques in welds recognition, based on signals obtained through in-line inspection tool called "smart pig" in Oil and Gas pipelines. The model uses a signal noise reduction phase by means of pre-processing algorithms and attribute-selection techniques. The noise reduction techniques were selected after a literature review and testing with survey data. Subsequently, the model was trained using recognition and classification algorithms, specifically artificial neural networks and support vector machines. Finally, the trained model was validated with different data sets and the performance was measured with cross validation and ROC analysis. The results show that is possible to identify welding automatically with an efficiency between 90 and 98 percent.

Fault diagnosis of localized bearing defects under non-weight-dominant conditions is studied in this paper. A theoretical model with eight degrees of freedom is established, considering two transverse vibrations of the rotor and bearing raceway and one high-frequency resonant degree of freedom. Both the Hertzian contact between rolling elements and raceways, bearing clearance, unbalance force and self-weight of rotor are taken into account in the model. The localized defects in both inner and outer raceways are modeled as half sinusoidal waves. Then, the theoretical model is solved numerically and the vibrational responses are obtained. Through envelope analysis, the fault characteristic frequencies of inner/outer raceway defects for various conditions, including the weight-dominant condition and non-weight-dominant condition, are presented and compared with each other.

Order tracking is one of the most effective algorithms to eliminate the effect of time-varying rotational speed on the rotary machines. However, this algorithm is not suitable for the faulty rolling bearing unless the peak time of the fault-induced impulse is set as zero which cannot be met in the real engineering. The traditional resampling process will cause uneven intervals between the adjacent impulse peaks in the angular domain and then affect the envelope analysis-based diagnosis result. To solve this problem, a new resampling algorithm with three parts is proposed: (a) linearly fitting the instantaneous rotational speed measured by the tachometer, (b) resampling the vibration signal from the time domain to the angular domain using the traditional method, (c) calculating the envelope deformation amount and then compensating the resampled result. The effectiveness of the proposed method has been validated by both the simulated and experimental bearing vibration signals.

The stability of friction disc could be seriously affected by the tooth surface damage due to poor working conditions of the wet multi-disc brake in heavy trucks. There are few current works focused on the damage of the friction disc caused by torsion-vibration impacts. Hence, it is necessary to investigate its damage mechanisms and evaluation methods. In this paper, a damage mechanism description and evaluation method of a friction disc based on the high-speed photography and tooth-root stress coupling is proposed. According to the HighSpeed Photography, the collision process between the friction disc and hub is recorded, which can be used to determine the contact position and deformation. Combined with the strain-stress data obtained by the strain gauge at the place of the tooth-root, the impact force and property are studied. In order to obtain the evaluation method, the damage surface morphology data of the friction disc extracted by 3D Super Depth Digital Microscope (VH-Z100R) is compared with the impact force and property. The quantitative relationships between the amount of deformation and collision number are obtained using a fitting analysis method. The experimental results show that the damage of the friction disc can be evaluated by the proposed impact damage evaluation method based on the high-speed photography and tooth-root stress coupling.

This paper presents a vibration based structural health monitoring methodology for damage assessment on wind turbine blades made of composite laminates. Normally, wind turbine blades are manufactured by two half shells made by composite laminates which are glued together. This connection must be carefully controlled due to its high probability to disbond which might result in collapse of the whole structure. The delamination between both parts must be monitored not only for detection but also for localisation and severity determination. This investigation consists in a real time monitoring methodology which is based on singular spectrum analysis (SSA) for damage and delamination detection. SSA is able to decompose the vibratory response in a certain number of components based on their covariance distribution. These components, known as Principal Components (PCs), contain information about of the oscillatory patterns of the vibratory response. The PCs are used to create a new space where the data can be projected for better visualization and interpretation. The method suggested is applied herein for a wind turbine blade where the free-vibration responses were recorded and processed by the methodology. Damage for different scenarios viz different sizes and locations was introduced on the blade. The results demonstrate a clear damage detection and localization for all damage scenarios and for the different sizes.

All commonly used condition monitoring systems (CMS) enable defining alarm thresholds that enhance efficient surveillance and maintenance of dynamic state of machinery. The thresholds are imposed on the measured values such as vibration-based indicators, temperature, pressure, etc. For complex machinery such as wind turbine (WT) the total number of thresholds might be counted in hundreds multiplied by the number of operational states. All the parameters vary not only due to possible machinery malfunctions, but also due to changes in operating conditions and these changes are typically much stronger than the former ones. Very often, such a behavior may lead to hundreds of false alarms. Therefore, authors propose a novel approach based on parameterized description of the threshold violation. For this purpose the novelty and severity factors are introduced. The first parameter refers to the time of violation occurrence while the second one describes the impact of the indicator-increase to the entire machine. Such approach increases reliability of the CMS by providing the operator with the most useful information of the system events. The idea of the procedure is presented on a simulated data similar to those from a wind turbine.

In this study, time series analysis and pattern recognition analysis are used effectively for the purposes of rolling bearing fault diagnosis. The main part of the suggested methodology is the autoregressive (AR) modelling of the measured vibration signals. This study suggests the use of a linear AR model applied to the signals after they are stationarized. The obtained coefficients of the AR model are further used to form pattern vectors which are in turn subjected to pattern recognition for differentiating among different faults and different fault sizes. This study explores the behavior of the AR coefficients and their changes with the introduction and the growth of different faults. The idea is to gain more understanding about the process of AR modelling for roller element bearing signatures and the relation of the coefficients to the vibratory behavior of the bearings and their condition.

The tuned vibration absorber (TVA) has been an effective tool for vibration control. However, the application of TVA can cause resonance of the primary system and increase its vibration when the absorber is mistuned. In this paper, a novel control strategy based on adaptive tuned vibration absorber (ATVA) of variable mass is proposed to reduce the resonance of the primary system. Unlike most ATVAs suggested by other researchers which adjust the absorber natural frequency by changing the stiffness, the variable mass ATVA varies its natural frequency by changing absorber mass to match the excitation frequency. Some simulations and experiments were conducted to test the performance of the control strategy. The results show that the proposed control plan can widen the frequency bandwidth of the absorber, as well as suppress the resonance of the primary system significantly. This implies that the work is useful for practical applications of ATVA.

This paper proposes an active vibration control technique, which is based on Fuzzy Modal Control, as applied to a piezoelectric actuator bonded to a composite structure forming a so-called smart composite structure. Fuzzy Modal Controllers were found to be well adapted for controlling structures with nonlinear behavior, whose characteristics change considerably with respect to time. The smart composite structure was modelled by using a so called mixed theory. This theory uses a single equivalent layer for the discretization of the mechanical displacement field and a layerwise representation of the electrical field. Temperature effects are neglected. Due to numerical reasons it was necessary to reduce the size of the model of the smart composite structure so that the design of the controllers and the estimator could be performed. The role of the Kalman Estimator in the present contribution is to estimate the modal states of the system, which are used by the Fuzzy Modal controllers. Simulation results illustrate the effectiveness of the proposed vibration control methodology for composite structures.

Transversal cracks in structures affect their stiffness as well as the natural frequency values. This paper presents a research performed to find the way how frequencies of sandwich beams change by the occurrence of damage. The influence of the locally stored energy, for ten transverse vibration modes, on the frequency shifts is derived from a study regarding the effect of stiffness decrease, realized by means of the finite element analysis. The relation between the local value of the bending moment and the frequency drop is exemplified by a concrete case. It is demonstrated that a reference curve representing the damage severity exists whence any frequency shift is derivable in respect to damage depth and location. This curve is obtained, for isotropic and multi-layer beams as well, from the stored energy (i.e. stiffness decrease), and is similar to that attained using the stress intensity factor in fracture mechanics. Also, it is proved that, for a given crack, irrespective to its depth, the frequency drop ratio of any two transverse modes is similar. This permitted separating the effect of damage location from that of its severity and to define a Damage Location Indicator as a sequence of squared of the normalized mode shape curvatures.

Ballistic damage of hybrid woven-fabric composites made of plain-weave E-glass- fabric/epoxy and 8H satin-weave T300 carbon-fabric/epoxy is studied using a combination of experimental tests, microstructural studies and finite-element (FE) analysis. Ballistic tests were conducted with a single-stage gas gun. Fibre damage and delamination were observed to be dominating failure modes. A ply-level FE model was developed, with a fabric-reinforced ply modelled as a homogeneous orthotropic material with capacity to sustain progressive stiffness degradation due to fibre/matrix cracking, fibre breaking and plastic deformation under shear loading. Simulated damage patterns on the front and back faces of fabric-reinforced composite plates provided an insight into their damage mechanisms under ballistic loading.

Fibrous networks are ubiquitous: they can be found in various engineering applications as well as in biological tissues. Due to complexity of their random microstructure, anisotropic properties and large deformation, their modelling is challenging. Though, there are numerous studies in literature focusing either on numerical simulations of fibrous networks or explaining their damage mechanisms at micro or meso-scale, the respective models usually do not include actual random microstructure and failure mechanisms. The microstructure of fibrous networks, together with highly non-linear mechanical behaviourof their fibres, is a key to initiation of damage, its spatial localization and ultimate failure [1]. Numerical models available in literature are not capable of elucidating actual microstructure of the material and, hence, its influence on damage processes in fibrous networks. To emulate a real-life microstructure in a developed finite-element model, an orientation distribution function for fibresobtained from X-ray micro computed-tomography images was considered to provide actual alignment of fibres. To validate the suggested model, notched and unnotched rectangular specimens were experimentally tested. A good correlation between the experimental data and simulation results was observed. This study revealed a significant effect of a notch on damage evolution.

Near surface mounted (NSM) technique with fiber reinforced polymer (FRP) is becoming a common method in the strengthening of concrete beams. The availability of NSM FRP technique depends on many factors linked to materials and geometry - dimensions of the rods used, type of FRP material employed, rods' surface configuration, groove size - and to adhesion between concrete and FRP rods. In this paper detection of damage is investigated measuring the natural frequency values of beam in the case of free-free ends. Damage was due both to reduction of adhesion between concrete and carbon-FRP rectangular and circular rods and cracking of concrete under static bending tests on beams. Comparison between experimental and theoretical frequency values evaluating frequency changes due to damage permits to monitor actual behaviour of RC beams strengthened by NSM CFRP rods.

This work deals with the application to composite plates of the surface interpolation method (SIM) for damage localization. The procedure, which is a generalization to the two-dimensional case of the previously published Interpolation Damage Detection Method (IDDM), locates reductions of stiffness in two-dimensional structures such as plates. The method is based on the damage sensitive of a spline function accuracy in fitting the operational displacement shapes, relies on the so-called Gibbs' phenomenon for splines. This phenomenon occurs when a spline function interpolates discontinuous functions and consists in sharp oscillations and overshoots (values higher than those of the function to be interpolated) near a discontinuous point. The operational deformed shapes are recovered from frequency response functions (FRF's) measured at different locations of the structure during vibrations. The accuracy of the spline interpolation is measured by an error function defined as the difference between the measured and interpolated operational deformed shapes. At a certain location an increase (statistically meaningful) of the interpolation error, with respect to a reference configuration, points out a localized variation of the operational shapes thus revealing the existence of damage. The accuracy of the surface interpolation method is experimentally assessed by impact hammer tests on glass fiber/vinylester composite plates progressively damaged and using finite element numerical modelling.

Damage tolerance is a classical safety concept for the design of aircraft structures. Basically, this approach considers possible damages in the structure, predicts the damage growth under applied loading conditions and predicts the following decrease of the structural strength. As a fundamental result the damage tolerance approach yields the maximum inspection interval, which is the time a damage grows from a detectable to a critical level. The above formulation of the damage tolerance safety concept targets on metallic structures where the damage is typically a simple fatigue crack. Fiber-reinforced polymers show a much more complex damage behavior, such as delaminationsin laminated composites. Moreover, progressive damage in composites is often initiated by manufacturing defects. The complex manufacturing processes for composite structures almost certainly yield parts with defects, e.g. pores in the matrix or undulations of fibers. From such defects growing damages may start after a certain time of operation.

The demand to simplify or even avoid the inspection of composite structures has therefore led to a comeback of the traditional safe-life safety concept. The aim of the so-called safe-life flaw tolerance concept is a structure that is capable of carrying the static loads during operation, despite significant damages and after a representative fatigue load spectrum. A structure with this property does not need to be inspected, respectively monitored at all during its service life. However, its load carrying capability is thereby not fully utilized.

This article presents the possible refinement of the state-of-the-art safe-life flaw tolerance concept for composite structures towards a damage tolerance approach considering also the influence of manufacturing defects on damage initiation and growth. Based on fundamental physical relations and experimental observations the challenges when developing damage growth and residual strength curves are discussed.

The aim of this study is the prediction of the dynamic response of damaged laminated composite structures in the context of component mode synthesis. Hence, a method of damage localization of complex structures is proposed. The dynamic behavior of transversely isotropic layers is expressed through elasticity coupled with damage based on an existing macro model for cracked structures. The damage is located only in some regions of the whole structure, which is decomposed on substructures. The incremental linear dynamic governing equations are obtained by using the classical linear Kirchhoff-Love theory of plates. Then, considering the damage-induced nonlinearity, the obtained nonlinear dynamic equations are solved in time domain. However, a detailed finite element modelling of such structure on the scale of localized damage would generate very high computational costs. To reduce this cost, Component Mode Synthesis method (CMS) is used for modelling a nonlinear fine-scale substructure damaged, connected to linear dynamic models of the remaining substructures, which can be condensed and not updated at each iteration. Numerical results show that the mechanical properties of the structure highly change when damage is taken into account. Under an impact load, damage increases and reaches its highest value with the maximum of the applied load and then remains unchanged. Besides, the eigenfrequencies of the damaged structure decrease comparing with those of an undamaged one. This methodology can be used for monitoring strategies and lifetime estimations of hybrid complex structures due to the damage state is known in space and time.

With the increased use of composites for load-carrying structures, the ability to obtain strain and damage information is critical to maintain reliable structures in the field. A promising class of multifunctional composites with the ability to self-sense strain and/or damage is possible through the use of carbon fibers and carbon nanotubes. This paper presents a comparative study of two sensors for fiber-reinforced polymer composites: the sensors are the carbon fibers themselves, and a non-structural carbon nanotube (CNT) film applied through spray deposition. The changes in resistance of the sensors are compared under monotonic and cyclic flexural loading. Within the limits of this study and the current CNT sensor configuration, the carbon fibers are shown to have a higher sensitivity for strain and damage sensing. However, the CNT film appears to track the performance of GFRPs reasonably well for tensile strains.

The study examines the influence of through-thickness stitching on the damage response of thin cross-ply carbon/epoxy laminates subjected to low-velocity impacts. Instrumented impact tests were carried out on unstitched and polyethylene stitched laminates and the resulting damage was assessed in detail by X-radiography analyses. The results of the observations carried out during the experimental analyses are illustrated and discussed to identify the mechanical role played by through-thickness reinforcement and to highlight the influence of the laminate layup on the impact resistance of stitched laminates.

The application of Glass Fibre Reinforced Polymers (GFRP) in many branches of industry has been increasing steadily. Many research works focus on damage identification for structures made out of such materials. However, not only delaminations, cracks or other damage can have a negative influence of GFRP parts performance. Previous research proved that fluid absorption influences the mechanical performance of composites. GFRP parts can be contaminated by moisture or release agent during manufacturing, while fuel, hydraulic fluid and moisture ingression into the composite can be the in-service treats. In the reported research authors focus on moisture detection. There are numerous sources of moisture such as post manufacturing NDT inspection with ultrasonics coupled by water or exposition to moisture during transportation and in service. An NDT tool used for the research is a terahertz (THz) spectrometer. The device uses an electromagnetic radiation in the terahertz range (0.1-3 THz) and allows for reflection and transmission measurements. The spectrometer is equipped with moving table that allows for XY scanning of large objects such as GFRP panels. In the conducted research refractive indices were experimentally extracted from the materials of interest (water and GFRP). Time signals as well as C-scans were analysed for samples with moisture contamination. In order to be sure that the observed effects are related to moisture contamination reference measurements were conducted. The obtained results showed that the THz NDT technique can detect moisture hidden under a GFRP with multiple layers.

Carbon fibre reinforced polymers (CFRP) have been used significantly more in recent years due to their increased specific strength over aluminium structures. One major area in which their use has grown is the aerospace industry where many now use CFRP in their construction. One major problem with CFRP's is their low resistance to impacts. Structural health monitoring (SHM) aims to continually monitor a structure throughout its entire life and can allow aircraft owners to identify impact damage as it occurs. This means that it can be repaired prior to growth, saving weight with the repair and the time that aircraft is grounded. Two areas of SHM being researched are Acoustic Emission (AE) monitoring and AcoustoUltrasonics (AU) both based on an understanding of the propagation of ultrasonic waves. 3D Scanning laser vibrometry was used to monitor the propagation of AU waves with the aim of gaining a better understanding their interaction with delamination in carbon fibre reinforced polymers. Three frequencies were exited with a PZT transducer and the received signal analysed by a cross correlation method. The results from this and the vibrometer scans revealed 100 kHz as the most effective propagating frequency of the three. A high resolution scan was then conducted at this frequency where it could be seen that only the out of plane component of the wave interacted with the damage, in particular the A0 mode. A 3D Fast Fourier Transform was then plotted, which identified the most effective frequency as 160 kHz.

High strength fibre reinforced polymers (FRPs) are composite materials made of fibres such as carbon, aramid and/or glass, and a resin matrix. FRPs are commonly used for structural repair and strengthening interventions and exhibit high potential for applications to existing constructions, including heritage buildings. In regard to aramid fibres, uncertainties about the long-term behaviour of these materials have often made the designers reluctant to use them in structural engineering. The present study describes simple and non-destructive nonlinearity tests for assessing damage or degradation of structural properties in Kevlar fibres. This was obtained by using high precision measurements to detect small deviations in the dynamic response measured on fibres and ropes. The change in dynamic properties was then related to a damage produced by exposure of the sample to UV rays for a defined time period, which simulated long-term sun exposure. In order to investigate the sensitivity of such an approach to damage detection, non-linearity characterisation tests were conducted on aramid fibres in both damaged and undamaged states. With the purpose of carrying out dynamic tests on small fibre specimens, a dedicated instrumentation was designed and built in cooperation with the Metrology Laboratory of the Department of Electronics at the Politecnico di Torino.

This paper concerns the experimental analysis of nonlinear response features of a composite laminate plate for impact damage detection. The measurement procedure is based on the Scaling Subtraction Method (SSM) and consists in exciting the damaged specimen with two sinusoidal signals at different amplitude. The linearly rescaled response signal at low amplitude excitation is subtracted from the response at large amplitude excitation to extract the nonlinear signatures. The latter are analysed in the time domain to infer the presence of damage. Results are compared with frequency domain analyses using the nonlinear vibro-acoustic modulation technique (NWMS). Changes in amplitude and phase as well as modulation effects of the acquired responses are also monitored. Surface-bonded, low profile piezoceramic transducers are used for excitation and sensing. Both measurements techniques are applied to detect barely visible impact damage in laminate composite plate. Non-destructive penetrant-enhanced X-ray inspections are carried out to characterize the extent of internal damage. The behavior of the nonlinear features and the sensitivity of each technique are also investigated in the paper.

Separation mechanism of Space launch vehicles are used in various separation systems and pyrotechnic devices. The operation of these pyrotechnic devices generates Pyroshock that can cause failures in electronic components. The prediction of high frequency structural response, especially the shock response spectrum (SRS), is important. This paper presents a non-destructive visualization and simulation of linear explosive-induced Pyroshock using phase arrayed Laser-induced shock. The proposed method includes a laser shock test based on laser beam and filtering zone conditioning to predict the SRS of Pyroshock. A ballistic test based on linear explosive and non-contact Laser Doppler Vibrometers and a nondestructive Laser shock measurement using laser excitation and several PZT sensors, are performed using a carbon composite sandwich panel. The similarity of the SRS of the conditioned laser shock to that of the real explosive Pyroshock is evaluated with the Mean Acceleration Difference. The average of MADs over the two training points was 33.64%. And, MAD at verification point was improved to 31.99%. After that, experimentally found optimal conditions are applied to any arbitrary points in laser scanning area. Finally, it is shown that linear explosive-induced real Pyroshock wave propagation can be visualized with high similarity based on the proposed laser technology.

The ability to accurately locate damage in any given structure is a highly desirable attribute for an effective structural health monitoring system and could help to reduce operating costs and improve safety. This becomes a far greater challenge in complex geometries and materials, such as modern composite airframes. The poor translation of promising laboratory based SHM demonstrators to industrial environments forms a barrier to commercial up take of technology. The acoustic emission (AE) technique is a passive NDT method that detects elastic stress waves released by the growth of damage. It offers very sensitive damage detection, using a sparse array of sensors to detect and globally locate damage within a structure. However its application to complex structures commonly yields poor accuracy due to anisotropic wave propagation and the interruption of wave propagation by structural features such as holes and thickness changes. This work adopts an empirical mapping technique for AE location, known as Delta T Mapping, which uses experimental training data to account for such structural complexities. The technique is applied to a complex geometry composite aerospace structure undergoing certification testing. The component consists of a carbon fibre composite tube with varying wall thickness and multiple holes, that was loaded under bending. The damage location was validated using X-ray CT scanning and the Delta T Mapping technique was shown to improve location accuracy when compared with commercial algorithms. The onset and progression of damage were monitored throughout the test and used to inform future design iterations.

With significant interest growing in the ocean renewables sector, horizontal axis tidal current turbines are in a position to dominate the marketplace. The test devices that have been placed in operation so far have suffered from premature failures, caused by difficulties with structural strength prediction. The goal of this work is to develop methods of predicting the damage level in tidal turbines under their maximum operating tidal velocity. The analysis was conducted using the finite element software package Abaqus; shell models of three representative tidal turbine blades are produced. Different construction methods will affect the damage level in the blade and for this study models were developed with varying hydrofoil profiles. In order to determine the risk of failure, a user material subroutine (UMAT) was created. The UMAT uses the failure criteria designed by Alfred Puck to calculate the risk of fibre and inter-fibre failure in the blades. The results show that degradation of the stiffness is predicted for the operating conditions, having an effect on the overall tip deflection. The failure criteria applied via the UMAT form a useful tool for analysis of high risk regions within the blade designs investigated.

Fibre reinforced polymer (FRP) composites are fast becoming a highly utilised engineering material for high performance applications due to their light weight and high strength. Carbon fibre and other high strength fibres are commonly used in design of aerospace structures, wind turbine blades, etc. and potentially for propellant tanks of launch vehicles. For the aforementioned fields of application, stability of the material is essential over a wide range of temperature particularly for structures in hostile environments. Many studies have been conducted, experimentally, over the last decade to investigate the mechanical behaviour of FRP materials at varying subzero temperature. Likewise, tests on aging and cycling effect (room to low temperature) on the mechanical response of FRP have been reported. However, a relatively lesser focused area has been the mechanical behaviour of FRP composites under cryogenic environment. This article reports a finite element method of investigating the changes in the mechanical characteristics of an FRP material when temperature based analysis falls below zero. The simulated tests are carried out using a finite element package with close material properties used in the cited literatures. Tensile test was conducted and the results indicate that the mechanical responses agree with those reported in the literature sited.

The monitoring of the condition of the offshore wind turbine during its operational states offers the possibility of performing accurate assessments of the remaining life-time as well as supporting maintenance decisions during its entire life. The efficacy of structural monitoring in the case of the offshore wind turbine, though, is undermined by the practical limitations connected to the measurement system in terms of cost, weight and feasibility of sensor mounting (e.g. at muddline level 30m below the water level). This limitation is overcome by reconstructing the full-field response of the structure based on the limited number of measured accelerations and a calibrated Finite Element Model of the system. A modal decomposition and expansion approach is used for reconstructing the responses at all degrees of freedom of the finite element model. The paper will demonstrate the possibility to predict dynamic strains from acceleration measurements based on the aforementioned methodology. These virtual dynamic strains will then be evaluated and validated based on actual strain measurements obtained from a monitoring campaign on an offshore Vestas V90 3 MW wind turbine on a monopile foundation.

With the application of a clock-like sensor network, a local interrogation strategy is established to extend the reconstruction algorithm for the probabilistic inspection of damage (RAPID) into multiple defects identification. In this strategy, the monitoring area is divided into several monitoring subareas, and each subarea is covered by a particular sensor network. Local interrogations are then employed in each subarea using the associated network of sensing paths. Benefit from that, the artifacts arise from the intersection of key sensing paths associated with different defects may be absent completely from some monitoring subarea. With the application of a proper image fusion strategy, the artifacts would be reduced and the damage indications could be preserved. The algorithm is applied to an aluminum plate with two artificial through-thickness holes introduced. The results demonstrated that the RAPID algorithm with the application of local interrogations is capable of identifying multiple defects in plate-like structures.

The ageing, operational and ambient loadings have a great impact in the operational and maintenance cost of concrete structures. Their service life prolongation is of utmost importance and this can be efficiently achieved by using reliable and low-cost monitoring and self-healing techniques. In the present study, the ultrasonic pulse velocity (UPV) method using embedded small-size and low-cost piezoelectric PZT (lead zirconate titanate) ceramic transducers in concrete with self-healing properties is implemented for monitoring not only the setting and hardening phases of concrete since casting time, but also for the detection of damage initiation, propagation and recovery of integrity after healing. A couple of small-scale notched unreinforced concrete beams are subjected to mode-I fracture through three-point bending tests. After a 24-hour healing agent curing period, the beams are reloaded using the same loading scenario. The results demonstrate the excellent performance of the proposed monitoring technique during the hydration, damage generation and recovery periods.

This paper presents an application of Fibre Bragg Grating (FBG) sensors for Structural Health Monitoring (SHM) of offshore wind energy support structure model. The analysed structure is a tripod equipped with 16 FBG sensors.

From a wide variety of Operational Modal Analysis (OMA) methods Frequency Domain Decomposition (FDD) technique is used in this paper under assumption that the input loading is similar to a white noise excitation. The FDD method can be applied using different sets of sensors, i.e. the one which contains all FBG sensors and the other set of sensors localised only on a particular tripod's leg. The cases considered during investigation were as follows: damaged and undamaged scenarios, different support conditions. The damage was simulated as an dismantled flange on an upper brace in one of the tripod legs. First the model was fixed to an antishaker table and investigated in the air under impulse excitations. Next the tripod was submerged into water basin in order to check the quality of the measurement set-up in different environmental condition. In this case the model was excited by regular waves.

The present work reports results from an extensive set of measurements which has been performed in order to formulate standard method to remove temperature changes from impedance measurements. The other issue addressed here is the investigation of influence of boundary condition and temperature changes on electromechanical impedance measurement for structural member. Due to electromechanical coupling, changes in dynamic characteristics can be seen in electrical impedance of piezoelectric transducer. Two different systems have been used during this measurement process. System based on FBG sensors has been used for temperature changes measurement while PZT transducers mounted on the structure with impedance analyser were used for electrical parameters measurement. During research electrical impedance and resistance of piezoelectric transducer were measured in order to analyze changes in amplitude of peaks and the frequency shift of peaks due to temperature variations and different configurations of the beam.

The EU-FP7 project SPARTACUS, currently in progress, sees the international cooperation of several partners toward the design and implementation of a satellite based asset tracking for supporting emergency management in crisis operations. Due to the emergency environment, one has to rely on a low power consumption wireless communication. Therefore, the communication hardware and software must be designed to match requirements which can only be foreseen at the level of more or less likely scenarios. The latter aspect suggests a deep use of a simulator (instead of a real network of sensors) to cover extreme situations. The former power consumption remark suggests the use of a minimal computer (Raspberry Pi) as data collector. In this paper, the results of a broad simulation campaign are reported in order to investigate the accuracy of the received data and the global power consumption for each of the considered scenarios.

Piezoelectric transducers are widely utilized in Structural Health Monitoring (SHM). They are used both in guided wave-based and electromechanical impedance-based methods. Transducer debonding or unevenly distributed glue underneath the transducer reduce the performance and reliability of the SHM system. Therefore, quality assessment methods for glue layer need to be developed. In this paper, the authors present results obtained from two methods that allow the quality assessment of adhesive bonds of piezoelectric transducers.

The electromechanical impedance method is utilized to analyze transducer adhesive bonding. An improperly prepared bonding layer is a source for changes in the electromechanical impedance characteristics in comparison to a perfectly bonded transducer. In the resistance characteristics of the properly bonded transducer the resonance peaks of the structure were clearly visible. In the case when adhesive layer is not equally distributed under sensor, the amplitudes of structural resonance peaks are reduced. In the case of completely detached transducer, the structural resonance peaks disappear and only resonance peaks of the transducer itself are visible. These peaks (peaks of free transducer hanging on wires) are significantly larger than the resonance peaks of the investigated structure in the considered frequency interval.

The bonding layer shape is also analyzed using time-domain terahertz spectroscopy in reflection mode. This method allows to visualize the adhesive layer distribution based on C-scan analysis. C-scans of signals or envelope-detected signals can be used to estimate the area of proper adhesion between bonding agent and transducer and hence provides a more quantitative approach towards transducer inspection.

This article presents a novel method to simulate the sensor output response of a Fibre Bragg Grating (FBG) sensor when embedded in a host material (Composite material or adhesive), during a crack growing/damage event. A finite element model of the crack growth mechanisms was developed, and different fracture modes were addressed. Then an output algorithm was developed to predict the sensor spectrum change during the different stages of the crack growing. Thus, it is possible to identify specific phenomenon that will only happen within the proximity of a crack, as compression field ahead the crack or non-uniform strain, and then identify the presence of such damage in the structure. Experimental tests were conducted in order to validate this concept and support the model. The FBG sensor response model was applied in a delamination of a Wind Turbine trailing edge, to demonstrate the applicability of this technique to more complicated structures, and to be used as a structural health monitoring design tool.

With the increasing complexity of aircraft structures and materials there is an essential need to continually monitor the structure for damage. This also drives the requirement for optimizing the location of sensors for damage detection to ensure full damage detection coverage of the structure whilst minimizing the number of sensors required, hence reducing costs, weight and data processing.

An experiment was carried out to investigate the optimal sensor locations of an active sensor network for detecting adhesive disbonds of a stiffened panel. A piezoelectric transducer was coupled to two different stiffened aluminium panels; one healthy and one with a 25.4mm long disbond. The transducer was positioned at five individual locations to assess the effectiveness of damage detection at different transmission locations. One excitation frequency of 100kHz was used for this study.

The panels were scanned with a 3D scanning laser vibrometer which represented a network of 'ideal' receiving transducers. The responses measured on the disbonded panel were cross- correlated with those measured on the healthy panel at a large number of potential sensor locations. This generated a cost surface which a genetic algorithm could interrogate in order to find the optimal sensor locations for a given size of sensor network. Probabilistic techniques were used to consider multiple disbond location scenarios, in order to optimise the sensor network for maximum probability of detection across a range of disbond locations.

While the potential of offshore wind and wave energy devices is well established and accepted, operations and maintenance issues are still not very well researched or understood. In this regard, scaled model testing has gained popularity over time for such devices at various technological readiness levels. The dynamic response of these devices are typically measured by different instruments during such scaled tests but agreed sensor choice, measurement and placement guidelines are still not in place. This paper compared the dynamic responses of some of these sensors from a scaled ocean wave testing to highlight the importance of sensor measurement strategies. The possibility of using multiple, cheaper sensors of seemingly inferior performance as opposed to the deployment of a small number of expensive and accurate sensors are also explored. An energy aware adaptive sampling theory is applied to highlight the possibility of more efficient computing when large volumes of data are available from the tested structures. Efficient sensor measurement strategies are expected to have a positive impact on the development of an device at different technological readiness levels while it is expected to be helpful in reducing operation and maintenance costs if such an approach is considered for the devices when they are in operation.

The paper consists of two interdependent parts. The first part presents numerical simulations of output response of single Fibre Bragg Grating (FBG) sensor which is driven by homogeneous deformation along sensor length. The example of such sensor is FBG sensor glued at only two points. The grating length and modulation depth of the refractive index are the critical parameters contributing to performance of the FBG sensors. Numerical analysis allowed to select an appropriate FBG sensors which will be used in the impact detection problem. In the second part of the paper a novel strain rosette with specific sensor array used in impact localisation problem is discussed and presented. The experiment was carried out on thin composite plate with the use of pulse force excitation. The method is based on estimation of principal direction of perturbed travelling wave initiated at impact point and does not use any information about wave propagation velocity.

Strain gauges and strain measurements have been widely used in structural health monitoring (SHM) systems as a means of detecting and localizing damage, due to their higher sensitivity to local damage. These damage identification techniques normally use strain related measurements such as the mode curvature, strain frequency response function or strain energy as the main parameter to detect damage. However, damage detection techniques based on acceleration measurements have also been investigated in the past, using modal parameter comparison and other methodologies. In this paper, the use of vibration-based strain measurements for use in SHM systems will be evaluated, with the purpose of characterizing their higher sensitivity in damage detection, when compared to other vibration measurements, such as acceleration-based measurements. Since the choice and use of the most damage sensitive parameter can lead to a more sensitive and robust system, the assessment of the more suitable sensor and processing of information is very important. For this purpose, numerical and experimental examples will be discussed to evaluate the higher performance of the strain gauges.

Performance of any structural health monitoring algorithm relies heavily on good measurement data. Hence, it is necessary to employ robust faulty sensor detection approaches to isolate sensors with abnormal behaviour and exclude the highly inaccurate data in the subsequent analysis. The independent component analysis (ICA) is implemented to detect the presence of sensors showing abnormal behaviour. A normalized form of the relative partial decomposition contribution (rPDC) is proposed to identify the faulty sensor. Both additive and multiplicative types of faults are addressed and the detectability illustrated using a numerical and an experimental example. An empirical method to establish control limits for detecting and identifying the type of fault is also proposed. The results show the effectiveness of the ICA and rPDC method in identifying faulty sensor assuming that baseline cases are available.

Due to their inherent, ability to provide structural information on a local level, mode shapes and t.lieir derivatives are utilized extensively for structural damage identification. Typically, more or less advanced mathematical methods are implemented to identify damage-induced discontinuities in the spatial mode shape signals, hereby potentially facilitating damage detection and/or localization. However, by being based on distinguishing damage-induced discontinuities from other signal irregularities, an intrinsic deficiency in these methods is the high sensitivity towards measurement, noise. The present, article introduces a damage localization method which, compared to the conventional mode shape-based methods, has greatly enhanced robustness towards measurement, noise. The method is based on signal processing of spatial mode shapes by means of continuous wavelet, transformation (CWT) and subsequent, application of a generalized discrete Teager-Kaiser energy operator (GDTKEO) to identify damage-induced mode shape discontinuities. In order to evaluate whether the identified discontinuities are in fact, damage-induced, outlier analysis of principal components of the signal-processed mode shapes is conducted on the basis of T²-statistics. The proposed method is demonstrated in the context, of analytical work with a free-vibrating Euler-Bernoulli beam under noisy conditions.

The dispersion of ultrasonic guided waves causes the energy of a signal to spread out in space and time as it propagates, which decreases the performance for damage detection significantly. A lot of signal processing methods have been proposed to reduce the effect of dispersion for this reason. In this paper, with the aim of developing an efficient methodology for high resolution Lamb wave inspection, a pulse compression and dispersion compensation method is established. In this method, broadband excitation and pulse compression technique are introduced to reconstruct the transform function with a high SNR. Subsequently, a scheme is established to alleviate the dispersion effects by performing compensation on the original narrowband excitation signals, and thus the time duration of received wave packet can be compressed during the extracting process. Finally, Numerical simulation and experiment are carried on aluminum specimens to investigate the behavior of the proposed method.

Under broadband excitation, the captured Lamb wave signals contain rich information of the structural properties. However, since multiple modes are highly dispersive and overlapped with each other, Lamb wave signals are especially complicated to be interpreted. To overcome this problem, a mode purification strategy is established under pseudo-pulse excitation. In this strategy, a pseudo-pulse excitation technique is introduced to obtain a high resolution for the inspection firstly. Dispersion compensation method is applied to remove the dispersion of the received signal subsequently, through which all the wave packets associated with the interferential mode propagating through different paths could be compressed into the same shape as the excitation. Benefiting from that, the energy of the wave packets corresponding to the interference mode could be concentrated in time domain as individual temporal pulses, which thereby could be eliminated by zero-amplitude rectangular time windows without affecting the desired mode much. After that, the inverse dispersion compensation is applied to the residual signals to restore the original waveform of the desired mode. Finally, experiments are introduced to validate the availability and robustness of the proposed strategy.

Mechanical vibration signal denoising has been an import problem for machine damage assessment and health monitoring. Wavelet transfer and sparse reconstruction are the powerful and practical methods. However, those methods are based on the fixed basis functions or atoms. In this paper, a novel method is presented. The atoms used to represent signals are learned from the raw signal. And in order to satisfy the requirements of real-time signal processing, an online dictionary learning algorithm is adopted. Orthogonal matching pursuit is applied to extract the most pursuit column in the dictionary. At last, denoised signal is calculated with the sparse vector and learned dictionary. A simulation signal and real bearing fault signal are utilized to evaluate the improved performance of the proposed method through the comparison with kinds of denoising algorithms. Then Its computing efficiency is demonstrated by an illustrative runtime example. The results show that the proposed method outperforms current algorithms with efficiency calculation.

A problem of rolling element bearings diagnostics for different machines is widely discussed in the literature. Most of the methods are based on the vibration signal analysis. However for some real signals the classical methods of damage detection are insufficient because of the specific nature of examined data. This specific nature is very often manifested through overlapping, mixing or interleaving of processes with different statistical properties and may be the result of different sources that have influence on the analysed signal. The problem of different sources identification and parametrisation of processes which are related to them is very challenging and requires advanced techniques. There are many methods which can be useful in this context however each signal should be analysed separately and there is no universal technique adequate to all possible time series. In this paper we propose a method of sources identification for vibration signal from the heavy duty crusher used in mineral processing plant. A crusher is a kind of machine which use a metal surface to crumble materials into small fractional pieces. During this process, as well as during entering material stream into the crusher, a lot of impacts appear. They are present in vibration signal acquired from bearings housing. Moreover, for some cases we also observe cyclic impulses which may be related to damage of rolling element bearings in the machine. The proposed sources identification method, especially useful for crushers vibrations, is based on the statistical analysis of examined data. Moreover by using advanced techniques of time series theory we propose a stochastic model that exhibits similar statistical properties as analysed signals. The introduced technique can be a starting point to damage detection of rolling element bearings of copper ore crushers.

Novelty detection is a widely used algorithm in different fields of study due to its capabilities to recognize any kind of abnormalities in a specific process in order to ensure better working in normal conditions. In the context of Structural Health Monitoring (SHM), this method is utilized as damage detection technique because the presence of defects can be considered as abnormal to the structure. Nevertheless, the performance of such a method could be jeopardized if the structure is operating in harsh environmental and operational conditions (EOCs). In this paper, novelty detection statistical technique is used to investigate the detection of damages under various EOCs. Experiments were conducted with different scenarios: damage sizes and shapes. EOCs effects were simulated by adding stochastic noise to the collected experimental data. Different levels of noise were studied to determine the accuracy and the performance of the proposed method.

Intelligent feature extraction and advanced signal processing techniques are necessary for a better interpretation of ultrasonic guided waves signals either in structural health monitoring (SHM) or in nondestructive testing (NDT). Such signals are characterized by at least multi-modal and dispersive components. In addition, in SHM, these signals are closely vulnerable to environmental and operational conditions (EOCs), and can be severely affected. In this paper we investigate the use of Artificial Neural Network (ANN) to overcome these effects and to provide a reliable damage detection method with a minimal of false indications. An experimental case of study (full scale pipe) is presented. Damages sizes have been increased and their shapes modified in different steps. Various parameters such as the number of inputs and the number of hidden neurons were studied to find the optimal configuration of the neural network.

This work presents a data driven approach for pipe leaks classification, validated on a steel carbon pipe section conditioned with leaks of different sizes and locations in order to emulate abnormal conditions. The tested structure was instrumented with piezoelectric devices attached at different locations over the surface, in order to induce guided waves and to record its behaviour along the structure. For each experiment, one piezo device is excited by means of a high frequency burst type signal and the other ones are used as sensors. A blind bridle is connected to one of the extremes and an air source is coupled to the other extreme to emulate operational conditions. Statistical indices of correlated piezoelectric signals are obtained by using principal component analysis to distinguish different leak scenarios. Next, a selforganizing map is used to classify them. The experimental results show an improvement of the classification-learning rate when correlated signals are used instead of uncorrelated ones

This paper discusses, experimental results of classifying several mass adding in a wing aircraft structure, using cross-correlated piezoelectric signals, represented by principal components. Piezoelectric signals are applied and recorded at specific points of the structure under analysis. Then, statistical features are obtained by means of principal component analysis to the correlation between excitation and response signals. Unsupervised learning is implemented to the reduced feature space, in order to identify clusters of damaged cases. The main result of this paper is the advantage resulting from using cross-correlated signals, evaluated through the performance of clustering indexes. Experimental data are collected from two test structures: i.) A turbine blade of a commercial aircraft and ii.) The skin panel of the torsion box of a wing. Damages are induced adding masses at different locations of the wing section surface. The results obtained show the effectiveness of the methodology to distinguish between different damage cases.

Image processing can be an important tool for inspecting underwater infrastructure elements like bridge piers and pile wharves. Underwater inspection often relies on visual descriptions of divers who are not necessarily trained in specifics of structural degradation and the information may often be vague, prone to error or open to significant variation of interpretation. Underwater vehicles, on the other hand can be quite expensive to deal with for such inspections. Additionally, there is now significant encouragement globally towards the deployment of more offshore renewable wind turbines and wave devices and the requirement for underwater inspection can be expected to increase significantly in the coming years. While the merit of image processing based assessment of the condition of underwater structures is understood to a certain degree, there is no existing protocol on such image based methods. This paper discusses and describes an image processing protocol for underwater inspection of structures. A stereo imaging image processing method is considered in this regard and protocols are suggested for image storage, imaging, diving, and inspection. A combined underwater imaging protocol is finally presented which can be used for a variety of situations within a range of image scenes and environmental conditions affecting the imaging conditions. An example of detecting marine growth is presented of a structure in Cork Harbour, Ireland.