Table of contents

Proceedings of 12th International Conference on Damage Assessment of Structures DAMAS 2017 Kitakyushu, Japan, 10-12 July 2017

Chairman

Prof. Magd Abdel Wahab

Ghent University, Belgium

Co-chairman

Prof. Nao-Aki Noda

Kyushu Institute of Technology, Japan

International organisation committee

Prof. Huajiang Ouyang, University of Liverpool, UK

Prof. Wieslaw Ostachowicz, Polish Academy of Sciences, Poland

Prof. Spilios Fassois, Patras University, Greece

Local Organizing Committee

Prof. N-A Noda, Kyushu Institute of Technology, Japan

Prof. H Sakamoto, Doshisha University, Japan

Prof. M Endo, Fukuoka University, Japan

Prof. M Goto, Oita University, Japan

Prof. C Makabe, University of Ryukyu, Japan

Vice-Pres. E Yamaguchi, Kyushu Institute of Technology, Japan

Prof. K Kosa, Kyushu Institute of Technology, Japan

Pres. N Sugano, FUJI P.S Corporation, Japan

Prof. K Oda, Oita University, Japan

Prof. G Hotta, National Institute of Technology, Ariake College, Japan

Prof. T Yakushiji, National Institute of Technology, Oita College, Japan

Prof. T Takase, Nagasaki University, Japan

Prof. M Hibino, Kyushu Institute of Technology, Japan

Prof. T Miyazaki, University of Ryukyu, Japan

Prof. T-C Chiu, National Cheng Kung University, Taiwan

Prof. K Masuda, University of Toyama, Japan

Prof. T Hattori, Shizuoka Institute of Science and Technology, Japan

Prof. S Nishida, Saga University, Japan

Dr. Y Sano, Kyushu Institute of Technology, Japan

Dr. Y Takase, Kyushu Institute of Technology, Japan

International Scientific Committee

F Aymerich, University of Cagliari, Italy

S K Bhalla, Indian Institute of Techonology Delhi, India

F Casciati, University of Pavia, Italy

R Ceravolo, Politechnico di Torino, Italy

F Chu, Tsinghua University, China

G De Roeck, KU Leuven, Belgium

L Faravelli, University of Pavia, Italy

S Fassois, Patras University, Greece

M Friswell, University of Swansea, UK

G-R Gillich, Eftimie Murgu Univ Resita, Romania

J-C Golinval, University of Liege, Belgium

A Gonzalez, University College Dublin, Ireland

K Holford, University of Cardiff, UK

MP Limongelli, Politecnico di Milano, Italy

G Manson, University of Sheffield, UK

T McCarthy, University of Wollongong, Australia

N-A Noda, Kyushu Institute of Technology, Japan

K Oda, Oita University, Japan

P Omenzetter, University of Aberdeen, UK

W Ostachowicz, Polish Academy of Science, Poland

H Ouyang, University of Liverpool, UK

B Peeters, LMS International, Belgium

R Pullin, Cardiff University, UK

A Rudawska, Lublin University of Technology, Poland

V Silberschmidt, University of Loughborough, UK

J J Sinou, Ecole Centrale de Lyon, France

C Surace, Politecnico di Torino, Italy

K Worden, University of Sheffield, UK

Y-L Zhou, National University of Singapore, Singapore

W Zhu, University of Maryland, Baltimore, USA

X Zhu, University of Western Sidney, Australia

Editorial

This volume contains the proceedings of the 12^th International Conference on Damage Assessment of Structures, DAMAS 2017, Kitakyushu, Japan, 10-12, July 2017. DAMAS has a long history of almost 22 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), 2013 (Dublin, Ireland) and 2015 (Ghent, Belgium). The twelfth edition of DAMAS conference series, DAMAS 2017, is hosted by Kyushu Institute of Technology, Japan, and is held at in the West Japan Industry and Trade Convention Association, located in the town centre of Kitakyushu city.

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 2017 are divided into 4 main sessions, namely 1) Structural Health and Condition Monitoring, 2) Damage in Civil Engineering, 3) Damage in Machineries and 4) Damage in Composite Materials.

The organising committee is grateful to keynote speakers; Prof Kunitomo Sugiura, Department of Civil and Earth Resources Engineering, Kyoto University, Japan, for his keynote lecture entitled 'Damage Assessment of Orthotropic Steel Bridge Decks', Prof Kikuo Kishimoto, Department of Transdisciplinary Science and Engineering, School of Environment and Society, Tokyo Institute of Technology, Japan, for his keynote lecture entitled 'Interfacial Mechanics for Multi-Material Structures' and Prof Stéphane Bordas, Faculté des Sciences, de la Technologie et de la Communication, Université du Luxembourg, for his keynote lecture entitled 'Multi-scale fracture simulations: model and discretisation error control'.

Special thanks go to members of the Scientific Committee of DAMAS 2017 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.

Finally, the organising committee would like to thank all authors, who have contributed to this volume and presented their research work at DAMAS 2017.

Professor Magd Abdel Wahab

Chairman of DAMAS 2017

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 classical vibration-based structural health monitoring evaluates damage via the analysis of single type measurement. The relationships between different types of measurements, however, are usually neglected. To address this problem, vibration data is to be analyzed in state space in this paper based on the the Poincare map method. The Poincare map method is an effective approach in damage detection. This method, however, requires the dependent measurements for displacement, velocity and acceleration, respectively. Based on the Fourier transform properties, a robust Poincare map method for damage detection is proposed based on the single type of measurement. Numerical and experimental verifications are employed to verify the effectiveness of the developed method. Compared with the classical numerical differential method, the present method is more accurate and robust to noise.

The vibration signals of mechanical components are non-linear and non-stationary and the feature frequencies of faulty bearings will be difficult extracted. This paper presents a new approach that combines the ensemble empirical mode decomposition (EEMD), the random decrement technique (RDT), and envelope spectrum for the fast detection of faults in bearings. The proposed approach uses the optimized and fast EEMD algorithm to extract intrinsic mode functions (IMFs) from vibration signals able to tack the feature frequency of bearings. If the Impulse response signal of the first IMF is unclear, it is further extracted by the RDT, and the feature frequencies are determined by analyzing the signals using envelope spectrum. The advantages of this method are its computational efficiency, and the strong non-stationary vibration signal decomposition and impulse signal extraction abilities. Numerical simulations and experimental data collected from faulty bearings are used to validate the proposed approach. The results show that the use of the EEMD, the RDT, and the envelope spectrum is a suitable and fast on-line strategy to detect faults of mechanical components.

Inclusion sizing, especially for large inclusions greater than 30μm provides important reference for metallurgical process control and fatigue life assessment of steel. Ultrasonic non-destructive testing (NDT) shows great advantages in detecting infrequently occurred large inclusions than eddy current, magnetic particle, microscopic or macroscopic examination procedures. In this paper, the performance of inclusion sizing by immersion ultrasonic C-scan imaging is studied numerically. A two-dimensional model that consists of spherically focused transducer, water couplant and steel with embedded inclusion is established and solved numerically by the finite element method. The signal intensity distributions of inclusion with different sizes are acquired and the effects of inclusion type, shape, orientation on signal intensity distribution are analysed. The results show that the 6dB-drop threshold has the smallest relative error compared with the 12dB-drop threshold and the full-drop threshold, which is better for determining inclusion size larger than 100μm. Experiment is also performed to validate the simulated results.

The Interpolation Method (IM) has been previously proposed and successfully applied for damage localization in plate like structures. The method is based on the detection of localized reductions of smoothness in the Operational Deformed Shapes (ODSs) of the structure. The IM can be applied to any type of structure provided the ODSs are estimated accurately in the original and in the damaged configurations. If the latter circumstance fails to occur, for example when the structure is subjected to an unknown input(s) or if the structural responses are strongly corrupted by noise, both false and missing alarms occur when the IM is applied to localize a concentrated damage. In order to overcome these drawbacks a modification of the method is herein investigated. An ODS is the deformed shape of a structure subjected to a harmonic excitation: at resonances the ODS are dominated by the relevant mode shapes. The effect of noise at resonance is usually lower with respect to other frequency values hence the relevant ODS are estimated with higher reliability. Several methods have been proposed to reliably estimate modal shapes in case of unknown input. These two circumstances can be exploited to improve the reliability of the IM. In order to reduce or eliminate the drawbacks related to the estimation of the ODSs in case of noisy signals, in this paper is investigated a modified version of the method based on a damage feature calculated considering the interpolation error relevant only to the modal shapes and not to all the operational shapes in the significant frequency range. Herein will be reported the comparison between the results of the IM in its actual version (with the interpolation error calculated summing up the contributions of all the operational shapes) and in the new proposed version (with the estimation of the interpolation error limited to the modal shapes).

To develop the protective devices for preventing traumatic brain injuries, it requires the accurate characterization of the mechanical properties of brain tissue. For this, it necessary to elucidate the effect of vitro preservation on the mechanical performance of brain tissue as usually the measurements are carried out in vitro. In this paper, the thermal behavior of brain tissue preserved for various period of time was first investigated and the mechanical properties were also measured. Both reveals the deterioration with prolonged preservation duration. The observations of brain tissue slices indicates the brain tissue experiences karyorrhexis and karyorrhexis in sequence, which accounts for the deterioration phenomena.

The key element of this work is to demonstrate alternative strategies for using pattern recognition algorithms whilst investigating structural health monitoring. This paper looks to determine if it makes any difference in choosing from a range of established classification techniques: from decision trees and support vector machines, to Gaussian processes. Classification algorithms are tested on adjustable synthetic data to establish performance metrics, then all techniques are applied to real SHM data. To aid the selection of training data, an informative chain of artificial intelligence tools is used to explore an active learning interaction between meaningful clusters of data.

A novel simple method using static test data for damage detection, localization, and quantification in beams is presented in this paper. The method is based on the change of the deflections of the beam between a reference and a damaged state. For simply supported beams with a single damage, the maximum value of the change of deflections indicates the location of damage. Once the damage is located, one could estimate the rotational stiffness at the damaged cross section by applying a superposition scheme to isolate the effect of damage and by using basic structural analysis equilibrium equations. Afterwards, damage extent is evaluated through an existing relation between rotational stiffness and damage severity. Several static tests of a simply supported steel beam with a point load at different locations were conducted to exam the performance of the strategy. The damage is artificially introduced as an opened crack located at the bottom of the beam. The deflections of the beam were measured by using a Digital Image Correlation system. The results show that the method can accurately detect and quantify the damage. The method is non-model based and can be easily conducted. No specific loading positions are required and damage identification objective can be achieved from just one single static test.

Investigation of fatigue strength of extruded AZ31 magnesium alloy was performed by ultrasonic fatigue tests (test frequency about 19500Hz) and taken to compare with conventional tension-compression fatigue tests (20Hz). The fatigue life under ultrasonic loading exhibits longer than the conventional one. Effects of ultrasonic frequency on the S-N curve, crack initiation and growth behaviour of AZ31 alloy is discussed. This work would be useful for improving the ultrasonic fatigue test method to observe the fatigue behaviour in very high cycle regime.

Vibration-based health monitoring of monumental structures must rely on efficient and, as far as possible, automatic modal analysis procedures. Relatively low excitation energy provided by traffic, wind and other sources is usually sufficient to detect structural changes, as those produced by earthquakes and extreme events. Above all, in-operation modal analysis is a non-invasive diagnostic technique that can support optimal strategies for the preservation of architectural heritage, especially if complemented by model-driven procedures. In this paper, the preliminary steps towards a fully automated vibration-based monitoring of the world's largest masonry oval dome (internal axes of 37.23 by 24.89 m) are presented. More specifically, the paper reports on signal treatment operations conducted to set up the permanent dynamic monitoring system of the dome and to realise a robust automatic identification procedure. Preliminary considerations on the effects of temperature on dynamic parameters are finally reported.

Spallation targets are the key components of accelerator driven systems (ADSs) that are being developed in the world. Erosion damages on the target vessels are anticipated. To prevent accidents occurrence due to erosion of spallation target vessel, the damage evaluation technique is desirable. The excited vibration of LBE target vessel will be monitored remotely to establish the technique. In this study, the basic researches were carried out through experiments and numerical simulations to investigate the interaction between ultrasonic waves and damage to understand the correlation between structural vibration and damage degree. Specimens with distributed erosion damage was irradiated by laser shots, and the vibration was detected by a laser vibrometer subsequently. A technique, Wavelet Differential Analysis (WDA), was developed to quantitatively and clearly indicate the differences caused by damage in the vibration signals. The results illustrated that the developed technique is sensitive to erosion damage with small size and is capable of quantitatively evaluating erosion damage. It is expected that the developed techniques can be applied to monitor the real spallation targets in the future.

Overhead transmission power lines are still one of the crucial elements of electro-energetic system. There are obvious advantages of using overhead transmission in the distribution of electricity. The amount of energy transported through a power line is determined by the distance between the wire and the ground or other objects placed beneath it (eg. trees). This distance is not fixed and depends on the overhang of the wire. This, in turn, is determined by many factors such as ambient temperature, humidity, precipitation, the value of current flowing through the wire. In order to optimize the wires electrical load, the monitoring of that overhang is required. One way to measure it is the non-contact measurement by vision system. It has the advantage, that using high-speed cameras respectively it also allows for vibration measurement and analysis of dynamic performance. That is very important while the wires are susceptible to the influence of wind, and the resulting vibrations interfere with the correct measurement of the overhang. The paper presents the results of vision measurements of the system vibrations and modal analysis carried out on their basis. The study was conducted on a specially made laboratory stand.

At present, substantial investments are being allocated to civil infrastructures also considered as valuable assets at a national or global scale. Structural Health Monitoring (SHM) is an indispensable tool required to ensure the performance and safety of these structures based on measured response parameters. The research to date on damage assessment has tended to focus on the utilization of wireless sensor networks (WSN) as it proves to be the best alternative over the traditional visual inspections and tethered or wired counterparts. Over the last decade, the structural health and behaviour of innumerable infrastructure has been measured and evaluated owing to several successful ventures of implementing these sensor networks. Various monitoring systems have the capability to rapidly transmit, measure, and store large capacities of data. The amount of data collected from these networks have eventually been unmanageable which paved the way to other relevant issues such as data quality, relevance, re-use, and decision support. There is an increasing need to integrate new technologies in order to automate the evaluation processes as well as to enhance the objectivity of data assessment routines. This paper aims to identify feasible methodologies towards the application of time-series analysis techniques to judiciously exploit the vast amount of readily available as well as the upcoming data resources. It continues the momentum of a greater effort to collect and archive SHM approaches that will serve as data-driven innovations for the assessment of damage through efficient algorithms and data analytics.

Frequency Response Function (FRF) residues have been widely used to update Finite Element models. They are a kind of original measurement information and have the advantages of rich data and no extraction errors, etc. However, like other sensitivity-based methods, an FRF-based identification method also needs to face the ill-conditioning problem which is even more serious since the sensitivity of the FRF in the vicinity of a resonance is much greater than elsewhere. Furthermore, for a given frequency measurement, directly using a theoretical FRF at a frequency may lead to a huge difference between the theoretical FRF and the corresponding experimental FRF which finally results in larger effects of measurement errors and damping. Hence in the solution process, correct selection of the appropriate frequency to get the theoretical FRF in every iteration in the sensitivity-based approach is an effective way to improve the robustness of an FRF-based algorithm. A primary tool for right frequency selection based on the correlation of FRFs is the Frequency Domain Assurance Criterion. This paper presents a new frequency selection method which directly finds the frequency that minimizes the difference of the order of magnitude between the theoretical and experimental FRFs. A simulated truss structure is used to compare the performance of different frequency selection methods. For the sake of reality, it is assumed that not all the degrees of freedom (DoFs) are available for measurement. The minimum number of DoFs required in each approach to correctly update the analytical model is regarded as the right identification standard.

Complex engineering problems require simulations, which are computationally expensive in cases of inverse identification tasks since they commonly requires hundreds of thousands of simulations. This paper propose a method based on model reduction for crack size estimation, combining the proper orthogonal decomposition method with radial basis functions. The reduced model is validated by comparing the obtained boundary displacements with the corresponding results from a finite element model. This inverse procedure is formulated as the minimization of the difference between the measured and computed values of displacement at selected boundary nodes, called sensor points, using particle swarm optimization algorithm. Convex and a non-convex specimens have been considered for investigations of crack presence, and identification of its size, different crack sizes have been tested to demonstrate the efficiency of the proposed approach.

Focusing on a rotor-bearing system with a breathing slant crack in the power transmission machine, influence of torsional excitations on the coupled nonlinear responses of the system is studied in this work. The slant crack element stiffness matrix is derived based on energy principal and the crack breathing phenomenon is simulated by the Crack Closure Line Position (CCLP) model; and the time-varying coupled dynamic equation of a rotor with a slant breathing crack considering the eccentricity of static unbalance is established using the finite element method and is solved by the NEWMARK method; then the influences of static torque and periodic torsional excitations on rotor dynamic responses in transverse and torsional directions are discussed. Results show that with the increment of static torque, cracks will become open gradually and the nonlinearity degree of rotors will increase firstly and then decrease. For periodic torsional excitation, the torsional excitation frequency and its rotating frequency combination can be found in transverse vibration response, and the larger is the amplitude of excitation, the larger are the combinational frequency components. Then a crack monitoring method for power transmission machines can be suggested by monitoring the coupled response characteristics and their variation from transverse responses of rotors before and after the loads change.

In this study, transmissibility based damage assessment techniques with vibration measurement are reviewed with highlighting the recent advancements since damage might induce severe changes and cause huge economic losses in both civil and mechanical engineering structures. In recent years, transmissibility underwent booming and divergent application for damage assessment both in experimental model and engineering application, and this review provides a fundamental understanding for transmissibility based damage assessment by summarizing those research outputs, which can serve as useful reference for further investigations.

In previous works, damage detection of metallic specimens exposed to temperature changes has been achieved by using a statistical baseline model based on Principal Component Analysis (PCA), piezodiagnostics principle and taking into account temperature effect by augmenting the baseline model or by using several baseline models according to the current temperature. In this paper a new approach is presented, where damage detection is based in a new index that combine Q and T² statistical indices with current temperature measurements. Experimental tests were achieved in a carbon-steel pipe of 1m length and 1.5 inches diameter, instrumented with piezodevices acting as actuators or sensors. A PCA baseline model was obtained to a temperature of 21º and then T² and Q statistical indices were obtained for a 24h temperature profile. Also, mass adding at different points of pipe between sensor and actuator was used as damage. By using the combined index the temperature contribution can be separated and a better differentiation of damages respect to undamaged cases can be graphically obtained.

Continuous monitoring for damage detection in structural assessment comprises implementation of low cost equipment and efficient algorithms. This work describes the stages involved in the design of a methodology with high feasibility to be used in continuous damage assessment. Specifically, an algorithm based on a data-driven approach by using principal component analysis and pre-processing acquired signals by means of cross-correlation functions, is discussed. A carbon steel pipe section and a laboratory tower were used as test structures in order to demonstrate the feasibility of the methodology to detect abrupt changes in the structural response when damages occur. Two types of damage cases are studied: crack and leak for each structure, respectively. Experimental results show that the methodology is promising in the continuous monitoring of real structures.

The algorithms commonly used for damage condition monitoring present several drawbacks related to unbalanced data, optimal training requirements, low capability to manage feature diversity and low tolerance to errors. In this work, an approach based on ensemble learning is discussed as alternative to obtain more efficient diagnosis. The main advantage of ensemble learning is the use of several algorithms at the same time for a better proficiency. Thereby, combining simplest tree decision algorithms in bagging scheme, the accuracy of damage detection is improved. It takes advantage by combining prediction of preliminary algorithms based on regression models. The methodology is experimentally validated on a carbon steel pipe section, where mass adding conditions are studied as possible failures. Data from an active system based on piezoelectric sensors are stored and characterized through the T² and Q statistical indexes. Then, they are the inputs to the ensemble learning. The proposed methodology allows determining the condition assessment and damage localizations in the structure. The results of the studied cases show the feasibility of ensemble learning for detecting occurrence of structural damages with successful results.

System identification performs as a core issue in structural dynamic analysis. In this study, transmissibility coherence is introduced for system identification with recalling the existing techniques based on transmissibility. Unlike previous approaches that require four-point measurement, the proposed methodology in this study only requires two-point measurement. The merit behind this approach is that the transmissibility coherence can be employed to estimate the subtraction of transmissibility between two reference points, by using auto- and cross-spectrum analysis. Verification using experimental data proves the feasibility of the proposed technique.

This paper aims to identify parameters of Bouc-Wen hysteretic model using time-domain measured data. It follows a general inverse identification procedure, that is, identifying model parameters is treated as an optimization problem with the nonlinear least squares objective function. Then, the enhanced response sensitivity approach, which has been shown convergent and proper for such kind of problems, is adopted to solve the optimization problem. Numerical tests are undertaken to verify the proposed identification approach.

Mode shapes or operational deflection shapes are highly sensitive to damage and can be used for multi-damage identification. Nevertheless, one drawback of this kind of methods is that the extracted spatial shape features tend to be compromised by noise, which degrades their damage identification accuracy, especially for incipient damage. To overcome this, joint approximate diagonalisation (JAD) also known as simultaneous diagonalisation is investigated to estimate mode shapes (MS's) statistically. The major advantage of JAD method is that it efficiently provides the common Eigen-structure of a set of power spectral density matrices. In this paper, a new criterion in terms of coefficient of variation (CV) is utilised to numerically demonstrate the better noise robustness and accuracy of JAD method over traditional frequency domain decomposition method (FDD). Another original contribution is that a new robust damage index (DI) is proposed, which is comprised of local MS distortions of several modes weighted by their associated vibration participation factors. The advantage of doing this is to include fair contributions from changes of all modes concerned. Moreover, the proposed DI provides a measure of damage-induced changes in 'modal vibration energy' in terms of the selected mode shapes. Finally, an experimental study is presented to verify the efficiency and noise robustness of JAD method and the proposed DI. The results show that the proposed DI is effective and robust under random vibration situations, which indicates that it has the potential to be applied to practical engineering structures with ambient excitations.

There are significant changes in vibration responses when various damages appear in structures. Therefore, structural vibration responses contain rich structure damage information. In this paper, virtual impulse response of structure under ambient excitation is obtained through the inversion of a transfer function, and is decomposed into components by wavelet packet transform. Then the energy of these wavelet packet components is calculated to obtain the wavelet packet energy spectrum. And a novel damage index i.e. Energy Spectrum Anomaly Measure is developed to identify the existence of damage. Damage extent can also be inferred from the relative value of Energy Spectrum Anomaly Measure at various locations. Numerical results are presented to evaluate the effectiveness and reliability of the proposed index. It is shown that the proposed damage index works well in identifying structure damages free from the effect of various excitation and there is a positive correlation between the index and the damage severity.

Seismic hazard analysis(SHA) is a key component of earthquake disaster prevention field for island engineering, whose result could provide parameters for seismic design microscopically and also is the requisite work for the island conservation planning's earthquake and comprehensive disaster prevention planning macroscopically, in the exploitation and construction process of both inhabited and uninhabited islands. The existing seismic hazard analysis methods are compared in their application, and their application and limitation for island is analysed. Then a specialized spatial analysis method of seismic hazard for island (SAMSHI) is given to support the further related work of earthquake disaster prevention planning, based on spatial analysis tools in GIS and fuzzy comprehensive evaluation model. The basic spatial database of SAMSHI includes faults data, historical earthquake record data, geological data and Bouguer gravity anomalies data, which are the data sources for the 11 indices of the fuzzy comprehensive evaluation model, and these indices are calculated by the spatial analysis model constructed in ArcGIS's Model Builder platform.

Vocal cord nodules represent a pathological condition for which the growth of unnatural masses on vocal folds affects the patients. Among other effects, changes in the vocal cords' overall mass and stiffness alter their vibratory behaviour, thus changing the vocal emission generated by them. This causes dysphonia, i.e. abnormalities in the patients' voice, which can be analysed and inspected via audio signals. However, the evaluation of voice condition through speech processing is not a trivial task, as standard methods based on the Fourier Transform, fail to fit the non-stationary nature of vocal signals. In this study, four audio tracks, provided by a volunteer patient, whose vocal fold nodules have been surgically removed, were analysed using a relatively new technique: the Hilbert-Huang Transform (HHT) via Empirical Mode Decomposition (EMD); specifically, by using the CEEMDAN (Complete Ensemble EMD with Adaptive Noise) algorithm. This method has been applied here to speech signals, which were recorded before removal surgery and during convalescence, to investigate specific trends. Possibilities offered by the HHT are exposed, but also some limitations of decomposing the signals into so-called intrinsic mode functions (IMFs) are highlighted. The results of these preliminary studies are intended to be a basis for the development of new viable alternatives to the softwares currently used for the analysis and evaluation of pathological voice.

A new static identification approach based on the minimum constitutive relation error (CRE) principle for beam structures is introduced. The exact stiffness and the exact bending moment are shown to make the CRE minimal for given displacements to beam damages. A two-step substitution algorithm—a force-method step for the bending moment and a constitutive-relation step for the stiffness—is developed and its convergence is rigorously derived. Identifiability is further discussed and the stiffness in the undeformed region is found to be unidentifiable. An extra set of static measurements is complemented to remedy the drawback. Convergence and robustness are finally verified through numerical examples.

In this research paper, the damage in Carbon Fibre Reinforced Polymer (CFRP) laminate beams under free vibration and simply supported conditions, is investigated numerically by Finite Element Method (FEM) using Matlab program. The developed Cornwell Indicator is used for damage detection and quantification in the considered composite beams. The data was acquired by developing a software that performs dynamic analysis of composite beams based on FEM. The results show that the efficiency of the developed indicator.

In this paper, the problem of using measured modal parameters to detect and locate damage in beam composite stratified structures with four layers of graphite/epoxy [0°/902°/0°] is investigated. A technique based on the residual force method is applied to composite stratified structure with different boundary conditions, the results of damage detection for several damage cases demonstrate that using residual force method as damage index, the damage location can be identified correctly and the damage extents can be estimated as well.

Active or pulsed thermography is a popular non-destructive testing (NDT) tool for inspecting the integrity and anomaly of industrial equipment. One of the recent research trends in using active thermography is to automate the process in detecting hidden defects. As of today, human effort has still been using to adjust the temperature intensity of the thermo camera in order to visually observe the difference in cooling rates caused by a normal target as compared to that by a sub-surface crack exists inside the target. To avoid the tedious human-visual inspection and minimize human induced error, this paper reports the design of an automatic method that is capable of detecting subsurface defects. The method used the technique of active thermography, edge detection in machine vision and smart algorithm. An infrared thermo-camera was used to capture a series of temporal pictures after slightly heating up the inspected target by flash lamps. Then the Canny edge detector was employed to automatically extract the defect related images from the captured pictures. The captured temporal pictures were preprocessed by a packet of Canny edge detector and then a smart algorithm was used to reconstruct the whole sequences of image signals. During the processes, noise and irrelevant backgrounds exist in the pictures were removed. Consequently, the contrast of the edges of defective areas had been highlighted. The designed automatic method was verified by real pipe specimens that contains sub-surface cracks. After applying such smart method, the edges of cracks can be revealed visually without the need of using manual adjustment on the setting of thermo-camera. With the help of this automatic method, the tedious process in manually adjusting the colour contract and the pixel intensity in order to reveal defects can be avoided.

Optimally deploy sparse sensors for better damage identification and structural health monitoring is always a challenging task. The Effective Independence(EI) is one of the most influential sensor placement method and to be discussed in the paper. Specifically, the effect of the different weighting coefficients on the maximization of the Fisher information matrix(FIM) and the physical significance of the re-orthogonalization of modal shapes through QR decomposition in the EI method are addressed. By analyzing the widely used EI method, we found that the absolute identification space put forward along with the EI method is preferable to ensuring the maximization of the FIM, instead of the original EI coefficient which was post-multiolied by a weighting matrix. That is, deleting the row with the minimum EI coefficient can't achieve the objective of maximizing the trace of FIM as initially conceived. Furthermore, we observed that in the computation of EI method, the sum of each retained row in the absolute identification space is a constant in each iteration. This potential property can be revealed distinctively by the product of target mode and its transpose, and its form is similar to an alternative formula of the EI method through orthogonal-triangular(QR) decomposition previously proposed by the authors. With it, the physical significance of re-orthogonalization of modal shapes through QR decomposition in the computation of EI method can be obviously manifested from a new perspective. Finally, two simple examples are provided to demonstrate the above two observations.

This paper presents the condition evaluation of bridge girders upgraded using post-tensioned near-surface-mounted (NSM) carbon fiber reinforced polymer (CFRP) strips subjected to corrosion damage. Computational models are developed to predict the behavior of the girders over a 100-year service period. Dynamic analysis exhibits that damage localization takes place, in conjunction with various mode shapes. As the extent of damage rises, the effectiveness of the NSM CFRP increases and the flexural stiffness of the girders decreases.

As one solution to the problem for condition assessment of existing short and medium span (10-30m) reinforced/prestressed concrete bridges, a new monitoring method using a public bus as part of a public transit system (called "Bus monitoring system") was 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. In this study, to evaluate the practicality of the newly developed bus monitoring system, it has been field-tested over a period of about four years by using an in-service fixed-route bus operating on a bus route in the city of Ube, Yamaguchi Prefecture, Japan. In here, although there are some useful monitoring methods for short and medium span bridges based on the qualitative or quantitative information, the sensitivity of damage detection was newly discussed for safety assessment based on long term health monitoring data. The verification results thus obtained are also described in this paper, and also evaluates the sensitivity of the "characteristic deflection", which is a bridge (health) condition indicator used by the bus monitoring system, in damage detection. Sensitivity of "characteristic deflection" is verified by introducing artificial damage into a bridge that has ended its service life and is awaiting removal. Furthermore, the sensitivity of "characteristic deflection" is verified by 3D FEM analysis.

Crack identification in multi-span beams is performed to determine whether the structure is healthy or not. Among all crack identification methods, these based on measured natural frequency changes present the advantage of simplicity and easy to use in practical engineering. To accurately identify the cracks characteristics for multi-span beam structure, a mathematical model is established, which can predict frequency changes for any boundary conditions, the intermediate supports being hinges. This relation is based on the modal strain energy concept. Since frequency changes are relative small, to obtain natural frequencies with high resolution, a signal processing algorithm based on superposing of numerous spectra is also proposed, which overcomes the disadvantage of Fast Fourier Transform in the aspect of frequency resolution. Based on above-mentioned mathematical model and signal processing algorithm, the method of identifying cracks on multi-span beams is presented. To verify the accuracy of this identification method, experimental examples are conducted on a two-span structure. The results demonstrate that the method proposed in this paper can accurately identify the crack position and depth.

In actual damage detection methods, localization and severity estimation can be treated separately. The severity is commonly estimated using fracture mechanics approach, with the main disadvantage of involving empirically deduced relations. In this paper, a damage severity estimator based on the global stiffness reduction is proposed. This feature is computed from the deflections of the intact and damaged beam, respectively. The damage is always located where the bending moment achieves maxima. If the damage is positioned elsewhere on the beam, its effect becomes lower, because the stress is produced by a diminished bending moment. It is shown that the global stiffness reduction produced by a crack is the same for all beams with a similar cross-section, regardless of the boundary conditions. One mathematical relation indicating the severity and another indicating the effect of removing damage from the beam. Measurements on damaged beams with different boundary conditions and cross-sections are carried out, and the location and severity are found using the proposed relations. These comparisons prove that the proposed approach can be used to accurately compute the severity estimator.

The number of well-preserved ancient buildings located in Shanxi Province, enjoying the absolute maximum proportion of ancient architectures in China, is about 18418, among which, 9053 buildings have the structural style of wood frame. The value of the application of BIM (Building Information Modeling) and GIS (Geographic Information System) is gradually probed and testified in the corresponding fields of ancient architecture's spatial distribution information management, routine maintenance and special conservation & restoration, the evaluation and simulation of related disasters, such as earthquake. The research objects are ancient architectures in JIN-FEN area, which were first investigated by Sicheng LIANG and recorded in his work of "Chinese ancient architectures survey report". The research objects, i.e. the ancient architectures in Jin-Fen area include those in Sicheng LIANG's investigation, and further adjustments were made through authors' on-site investigation and literature searching & collection. During this research process, the spatial distributing Geodatabase of research objects is established utilizing GIS. The BIM components library for ancient buildings is formed combining on-site investigation data and precedent classic works, such as "Yingzao Fashi", a treatise on architectural methods in Song Dynasty, "Yongle Encyclopedia" and "Gongcheng Zuofa Zeli", case collections of engineering practice, by the Ministry of Construction of Qing Dynasty. A building of Guangsheng temple in Hongtong county is selected as an example to elaborate the BIM model construction process based on the BIM components library for ancient buildings. Based on the foregoing work results of spatial distribution data, attribute data of features, 3D graphic information and parametric building information model, the information management system for ancient architectures in Jin-Fen Area, utilizing GIS&BIM technology, could be constructed to support the further research of seismic disaster analysis and seismic performance simulation.

The Impact-Echo method is known as a non-destructive testing for concrete structures. The technique is based on the use of low-frequency elastic waves that propagate in concrete to determine the thickness and to detect internal flaws in concrete. The presence and locations of defects in concrete are estimated from identifying peak frequencies in the frequency spectra, which are responsible for the resonance due to time-of-flight from the defects. In practical applications, however, obtained spectra include so many peak frequencies that it is fairly difficult to identify the defects correctly. In order to improve the Impact-Echo method, Stack Imaging of spectral amplitudes Based on Impact-Echo (SIBIE) procedure is developed as an imaging technique applied to the Impact-Echo data, where defects in concrete are identified visually at the cross-section. In this study, the SIBIE procedure is applied to identify the delamination in a concrete slab. It is demonstrated that the delamination can be identified with reasonable accuracy.

The electro-mobility is becoming an increasingly present reality in recent years. The most important drawback of this technology is known to be limited battery autonomy. In an attempt to overcome this problem, for specific studies and testing, a number of roads have been implemented with coil systems in order to transfer power to electric vehicles, as described in this article. While on the one hand this could solve the problem of charging, on the other hand the introduction of a technology within an existing infrastructure could result in further structural issues. Since little or no information on the possible structural effect of the introduction of a charging system in the road is currently available, this study has focused on the long-term fatigue analysis of an electric road infrastructure in which an inductive wireless charging system has been introduced into the road structure. To perform the fatigue analysis, a recursive procedure defined within a probabilistic framework was developed and applied to a benchmark case study. The results obtained from the analysis represent an initial database for the definition of strategies and protocols for the monitoring, maintenance and operations of future electric roads infrastructures.

This experimental investigation focuses on collecting vibration data after different loading scenarios in a PC girder while measuring the performance at the same time. The vibration data is used for modal analysis and since several samples were taken in each scenario with different impact hammer tips, a comparison of the outcomes is also possible. The performance is based on recorded displacements along the bottom surface of the girder, information that makes possible the calculation of energy absorbed before cracking and the energy dissipation that takes place after cracking. Furthermore, two major damage events, a tendon breakage and cracking, were induced and monitored respectively. This study also clarified the influence of change in energy on changes in modal parameters.

The growth of cities, the impacts of climate change and the massive cost of providing new infrastructure provide the impetus for TRUSS (Training in Reducing Uncertainty in Structural Safety), a €3.7 million Marie Skłodowska-Curie Action Innovative Training Network project funded by EU's Horizon 2020 programme, which aims to maximize the potential of infrastructure that already exists (http://trussitn.eu). For that purpose, TRUSS brings together an international, inter-sectoral and multidisciplinary collaboration between five academic and eleven industry institutions from five European countries. The project covers rail and road infrastructure, buildings and energy and marine infrastructure. This paper reports progress in fields such as advanced sensor-based structural health monitoring solutions – unmanned aerial vehicles, optical backscatter reflectometry, monitoring sensors mounted on vehicles, ... – and innovative algorithms for structural designs and short- and long-term assessments of buildings, bridges, pavements, ships, ship unloaders, nuclear components and wind turbine towers that will support infrastructure operators and owners in managing their assets.

An anisotropic damage model is developed based on conventional rotating crack approach. It uses nonlinear unloading/linear reloading branches to model the hysteretic behavior of concrete. Two damage variables, determined by the ratio of accumulated dissipating energy to fracture energy, are introduced to represent the stiffness degradation in tension and compression. Three cyclic tests are simulated by this model and sensitivity analyses are conducted as well. The numerical responses calculated by the damage model are consistent with those obtained from the experiments. The numerical results reflect the nonlinear behavior observed in those tests, such as the damage-induced stiffness degradation, accumulation of residual deformation, energy dissipation caused by hysteretic behavior and stiffness recovery effect due to crack closure. Sensitivity analyses show that the damage exponents have significant influence on the computational accuracy. It is concluded that the anisotropic damage model is applicable to the nonlinear analyses of concrete structures subjected to cyclic loading.

Proton exchange membrane fuel cell (PEMFC) stack usually undergoes various vibrations during packing, transportation and serving time, in particular for those used in the automobiles and portable equipment. Based on the Miner fatigue damage theory, the fatigue lives of the fuel cell components are first assessed. Then the component fatigue life contours of the stack are obtained under four working conditions, i.e. the three single-axial (in X-, Y- and Z-axis separately) and multi-axial random vibrations. Accordingly, the component damage under various vibrations is evaluated. The stress distribution on the gasket and PEM will greatly affect their fatigue lives. Finally, we compare the fatigue lives of 4-bolt- and 6-bolt-clamping stacks under the same total clamping force, and find that increasing the bolt number could improve the bolt fatigue lives.

The main problems in milling difficult-to-machine materials are the high cutting temperature and rapid tool wear. However it is impossible to investigate tool wear in machining. Tool wear and cutting chip formation are two of the most important representations for machining efficiency and quality. The purpose of this paper is to develop the model of tool wear with cutting chip formation (width of chip and radian of chip) on difficult-to-machine materials. Thereby tool wear is monitored by cutting chip formation. A milling experiment on the machining centre with three sets cutting parameters was performed to obtain chip formation and tool wear. The experimental results show that tool wear increases gradually along with cutting process. In contrast, width of chip and radian of chip decrease. The model is developed by fitting the experimental data and formula transformations. The most of monitored errors of tool wear by the chip formation are less than 10%. The smallest error is 0.2%. Overall errors by the radian of chip are less than the ones by the width of chip. It is new way to monitor and detect tool wear by cutting chip formation in milling difficult-to-machine materials.

Control of dynamic responses of renewable energy device platforms is important for their performance, safe operation and efficiency over their lifetime under regular and extreme wave conditions. Tuned Liquid Column Dampers (TLCDs) have been recently considered as a viable passive control mechanism in this regard but limited information is available in relation to their experimental performance. This paper compares scaled experiments conducted in two different ocean wave basins where floating offshore platforms were retrofitted with multiple TLCDs (MTLCDs). Performance of such MTLCDs in these scaled ocean wave basins are evaluated and compared considering control of dynamic responses for a specific objective. This paper shows the potential of MTLCDs to reduce motions in offshore platforms for different designs and platforms of MTLCDs and provides a comparison of the levels of reduction of dynamic responses achieved. The performance of MTLCDs in different wave basins create an experimental evidence base behind the potential use of such solutions, the objectives of such use and highlight related challenges and limitations.

With car manufacturers simultaneously facing increasing passive safety and efficiency requirements, FRP-metal hybrid material systems are one way to design lightweight and crashworthy vehicle structures. Generic automotive hybrid structural concepts have been tested under crash loading conditions. In order to assess the state of overall damage and structural integrity, and primarily to validate simulation data, several NDT techniques have been assessed regarding their potential to detect common damage mechanisms in such hybrid systems. Significant potentials were found particularly in combining 3D-topography laser scanning and X-Ray imaging results. Ultrasonic testing proved to be limited by the signal coupling quality on damaged or curved surfaces.

This paper presents a Topic Correlation Analysis (TCA) based approach for bearing fault diagnosis. In TCA, Joint Mixture Model (JMM), a model which adapts Probability Latent Semantic Analysis (PLSA), is constructed first. Then, JMM models the shared and domain-specific topics using "fault vocabulary" . After that, the correlations between two kinds of topics are computed and used to build a mapping matrix. Furthermore, a new shared space spanned by the shared and mapped domain-specific topics is set up where the distribution gap between different domains is reduced. Finally, a classifier is trained with mapped features which follow a different distribution and then the trained classifier is tested on target bearing data. Experimental results justify the superiority of the proposed approach over the stat-of-the-art baselines and it can diagnose bearing fault efficiently and effectively under variable operating conditions.

Classical bearing fault diagnosis methods, being designed according to one specific task, always pay attention to the effectiveness of extracted features and the final diagnostic performance. However, most of these approaches suffer from inefficiency when multiple tasks exist, especially in a real-time diagnostic scenario. A fault diagnosis method based on Non-negative Matrix Factorization (NMF) and Co-clustering strategy is proposed to overcome this limitation. Firstly, some high-dimensional matrixes are constructed using the Short-Time Fourier Transform (STFT) features, where the dimension of each matrix equals to the number of target tasks. Then, the NMF algorithm is carried out to obtain different components in each dimension direction through optimized matching, such as Euclidean distance and divergence distance. Finally, a Co-clustering technique based on information entropy is utilized to realize classification of each component. To verity the effectiveness of the proposed approach, a series of bearing data sets were analysed in this research. The tests indicated that although the diagnostic performance of single task is comparable to traditional clustering methods such as K-mean algorithm and Guassian Mixture Model, the accuracy and computational efficiency in multi-tasks fault diagnosis are improved.

This paper focused on the damage diagnosis for NC machine tools and put forward a damage diagnosis method based on hybrid Stationary subspace analysis (SSA), for improving the accuracy and visibility of damage identification. First, the observed single sensor signal was reconstructed to multi-dimensional signals by the phase space reconstruction technique, as the inputs of SSA. SSA method was introduced to separate the reconstructed data into stationary components and non-stationary components without the need for independency and prior information of the origin signals. Subsequently, the selected non-stationary components were analysed for training LS-SVM (Least Squares Support Vector Machine) classifier model, in which several statistic parameters in the time and frequency domains were exacted as the sample of LS-SVM. An empirical analysis in NC milling machine tools is developed, and the result shows high accuracy of the proposed approach.

As an important part of national energy supply system, transmission pipelines for natural gas are possible to cause serious environmental pollution, life and property loss in case of accident. The third party damage is one of the most significant causes for natural gas pipeline system accidents, and it is very important to establish an effective quantitative risk assessment model of the third party damage for reducing the number of gas pipelines operation accidents. Against the third party damage accident has the characteristics such as diversity, complexity and uncertainty, this paper establishes a quantitative risk assessment model of the third party damage based on Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE). Firstly, risk sources of third party damage should be identified exactly, and the weight of factors could be determined via improved AHP, finally the importance of each factor is calculated by fuzzy comprehensive evaluation model. The results show that the quantitative risk assessment model is suitable for the third party damage of natural gas pipelines and improvement measures could be put forward to avoid accidents based on the importance of each factor.

The dependency of the tensile strength ${\sigma }_{{\rm{B}}}^{\mathrm{smooth}}$ and the notch strength ${\sigma }_{{\rm{B}}}^{\mathrm{notch}}$ on strain rate and temperature were investigated for conventional ferrite-pearlite type ductile cast iron (JIS-FCD500) to make clear the applicability of ductile cast iron to components for welded steel structures. High speed tensile tests were conducted on notched and smooth specimens with varying strain rate and temperature. Charpy absorbed energy was also evaluated on notched specimen with varying temperature. It is found that the tensile strength is in a good relationship with strain rate-temperature parameter R for the wide range of strain rate and temperature. With decreasing R parameter, both ${\sigma }_{{\rm{B}}}^{\mathrm{smooth}}$ and ${\sigma }_{{\rm{B}}}^{\mathrm{notch}}$ increase even when Charpy absorbed energy starts decreasing. It should be noted that the notch strength ${\sigma }_{{\rm{B}}}^{\mathrm{notch}}$ is always larger than the tensile strength at room temperature ${\sigma }_{{\rm{B}},\,\mathrm{RT}}^{\mathrm{smooth}}$ in the range of R parameter required for the welded structures. Therefore, the tensile strength ${\sigma }_{{\rm{B}},\,\mathrm{RT}}^{{\rm{smooth}}}$ is confirmed to be useful for the structural design.

Several ceramic rolls can be used efficiently to produce high quality zinc coated steel sheet used for automobiles. Those ceramics rolls may provide a longer life and reduce the cost for the maintenance because of its large heat resistance and large wear resistance. One example may be seen in sink rolls used in molten zinc bath to manufacture zinc coated steel sheet. Since the rolls are subjected to large thermal stress and mechanical loading, care should be taken for the risk of fracture due to the ceramic brittleness. Moreover, since the sleeve and shafts can be connected only by using small shrink fitting ratio, another failure risk should be considered for the separation of those components [25, 26]. In this paper, therefore, the mechanical and thermal stress and separation condition will be investigated considering the separation of the connected portion. Here, by using the finite volume method the heat transfer coefficient is discussed and by using the finite element method the thermal stress is considered.

Ceramic roller can be used in the heating furnace conveniently because of its high temperature resistance. The roller consists of sleeve and steel shaft connected only under a small shrink fitting ratio because of the brittleness. However, the coming out of the shaft may often happen from the ceramic sleeve under repeated bending load. Therefore, how to prevent the coming out failure becomes an important issue. Based on the previous study, a two-dimensional shrink fitted structure is considered by replacing the shaft with the inner plate and by replacing the sleeve with the outer plate. Then, this research focuses on preventing the inner plate coming out from the outer plate by introducing a newly designed stopper on the outer plate. The simulation results shows that the coming out phenomenon can be prevented effectively due to the contact between the inter plate and the stopper installed on the outer plate. In order to evaluate the contact force between the inner plate and the stopper, the coming out mechanism is clarified. To prevent the coming out by stopper safely, the effects of the magnitude of repeated load and the friction coefficient upon the contact compressive force are investigated under large number of loading cycles by using 2D simulation.

Particularly offshore there is a trend to cluster wind turbines in large wind farms, and in the near future to operate such a farm as an integrated power production plant. Predictability of individual turbine behavior across the entire fleet is key in such a strategy. Failure of turbine subcomponents should be detected well in advance to allow early planning of all necessary maintenance actions; Such that they can be performed during low wind and low electricity demand periods. In order to obtain the insights to predict component failure, it is necessary to have an integrated clean dataset spanning all turbines of the fleet for a sufficiently long period of time. This paper illustrates our big-data approach to do this. In addition, advanced failure detection algorithms are necessary to detect failures in this dataset. This paper discusses a multi-level monitoring approach that consists of a combination of machine learning and advanced physics based signal-processing techniques. The advantage of combining different data sources to detect system degradation is in the higher certainty due to multivariable criteria. In order to able to perform long-term acceleration data signal processing at high frequency a streaming processing approach is necessary. This allows the data to be analysed as the sensors generate it. This paper illustrates this streaming concept on 5kHz acceleration data. A continuous spectrogram is generated from the data-stream. Real-life offshore wind turbine data is used. Using this streaming approach for calculating bearing failure features on continuous acceleration data will support failure propagation detection.

Most processing tools based on frequency analysis of vibration signals are only applicable for stationary speed regimes. Speed variation causes the spectral content to smear, which encumbers most conventional fault detection techniques. To solve the problem of non-stationary speed conditions, the instantaneous angular speed (IAS) is estimated. Wind turbine gearboxes however are typically multi-stage gearboxes, consisting of multiple shafts, rotating at different speeds. Fitting a sensor (e.g. a tachometer) to every single stage is not always feasible. As such there is a need to estimate the IAS of every single shaft based on the vibration signals measured by the accelerometers. This paper investigates the performance of the multi-order probabilistic approach for IAS estimation on experimental case studies of wind turbines. This method takes into account the meshing orders of the gears present in the system and has the advantage that a priori it is not necessary to associate harmonics with a certain periodic mechanical event, which increases the robustness of the method. It is found that the MOPA has the potential to easily outperform standard band-pass filtering techniques for speed estimation. More knowledge of the gearbox kinematics is beneficial for the MOPA performance, but even with very little knowledge about the meshing orders, the MOPA still performs sufficiently well to compete with the standard speed estimation techniques. This observation is proven on two different data sets, both originating from vibration measurements on the gearbox housing of a wind turbine.

The problem of identification of non-linear phenomena associated with contact–type non-linearity is the subject of many research papers. The number of theoretical models describing the non-linear phenomena is constantly increasing. New capabilities of experimental verification and observation of these non-linear effects provide opportunities for a more accurate mathematical description of the non-linear behavior of contact interfaces. Better understanding of the non-linear related contact mechanisms can lead to more accurate numerical models of structures with contact-types defects, damage propagation and prediction algorithms and development of new methods for damage detection. This paper presents research on the non-linear acoustic phenomena in the presence of contact–type damage. Two test samples in contact are subject to vibro-acoustic modulation test. Non-linear spectral components were analysed and compared to the temperature changes generated as a results of the frictional forces.

For the fault classification model based on extreme learning machine (ELM), the diagnosis accuracy and stability of rolling bearing is greatly influenced by a critical parameter, which is the number of nodes in hidden layer of ELM. An adaptive adjustment strategy is proposed based on vibrational mode decomposition, permutation entropy, and nuclear kernel extreme learning machine to determine the tunable parameter. First, the vibration signals are measured and then decomposed into different fault feature models based on variation mode decomposition. Then, fault feature of each model is formed to a high dimensional feature vector set based on permutation entropy. Second, the ELM output function is expressed by the inner product of Gauss kernel function to adaptively determine the number of hidden layer nodes. Finally, the high dimension feature vector set is used as the input to establish the kernel ELM rolling bearing fault classification model, and the classification and identification of different fault states of rolling bearings are carried out. In comparison with the fault classification methods based on support vector machine and ELM, the experimental results show that the proposed method has higher classification accuracy and better generalization ability.

Type IV creep damage is the phenomena that a large number of voids in micron size initiate, grow, coalesce each other and become large cracks. They initiate in welded joints of high chromium steel in power plant. The density of voids, the number of voids per a unit area, is used to evaluate the residual life. The observed density of voids depends on the observation conditions; the observation area and the magnification of observed photograph of metallographic structure, because voids do not distribute uniformly and the small magnification misses the small voids. In previous study, we studied the influence of them with simulated fine-grain HAZ of Mod.9Cr-1Mo steel, and proposed how to determine the appropriate observation area for the temporary allowable error. We also proposed the method to evaluate the start time of initiation of voids, the initiation rate of voids and the growth rate of voids based on the relation between the observed density of voids and the magnification. But the experimental data was short. In this paper we showed new data, but they were yet not sufficient. We used FEM analysis and considered why enough data had been not taken.

Roll grinder is one of the important parts in the rolling machinery, and the grinding precision of roll surface has direct influence on the surface quality of steel strip. However, during the grinding process, the centre bears the gravity of the roll and alternating stress. Therefore, wear or spalling faults are easily observed on the centre, which will lead to an anomalous vibration of the roll grinder. In this study, a resonance demodulation scheme is proposed to detect the centre wear fault of roll grinder. Firstly, fast kurtogram method is employed to help select the sub-band filter parameters for optimal resonance demodulation. Further, the envelope spectrum are derived based on the filtered signal. Finally, two health indicators are designed to conduct the fault diagnosis for centre wear fault. The proposed scheme is assessed by analysing experimental data from a roll grinder of twenty-high rolling mill. The results show that the proposed scheme can effectively detect the centre wear fault of the roll grinder.

There have been many recent developments in the application of data-based methods to machine condition monitoring. A powerful methodology based on machine learning has emerged, where diagnostics are based on a two-step procedure: extraction of damage-sensitive features, followed by unsupervised learning (novelty detection) or supervised learning (classification). The objective of the current pair of papers is simply to illustrate one state-of-the-art procedure for each step, using synthetic data representative of reality in terms of size and complexity. The first paper in the pair will deal with feature extraction.

Although some papers have appeared in the recent past considering stochastic resonance as a means of amplifying damage information in signals, they have largely relied on ad hoc specifications of the resonator used. In contrast, the current paper will adopt a principled optimisation-based approach to the resonator design. The paper will also show that a discrete dynamical system can provide all the benefits of a continuous system, but also provide a considerable speed-up in terms of simulation time in order to facilitate the optimisation approach.

There have been many recent developments in the application of data-based methods to machine condition monitoring. A powerful methodology based on machine learning has emerged, where diagnostics are based on a two-step procedure: extraction of damage-sensitive features, followed by unsupervised learning (novelty detection) or supervised learning (classification). The objective of the current pair of papers is simply to illustrate one state-of-the-art procedure for each step, using synthetic data representative of reality in terms of size and complexity. The second paper in the pair will deal with novelty detection. Although there has been considerable progress in the use of outlier analysis for novelty detection, most of the papers produced so far have suffered from the fact that simple algorithms break down if multiple outliers are present or if damage is already present in a training set. The objective of the current paper is to illustrate the use of phase-space thresholding; an algorithm which has the ability to detect multiple outliers inclusively in a data set.

In order to make an accurate state evaluation of oil pump unit, a comprehensive evaluation index should be established. A multi-parameters state evaluation method of oil pump unit is proposed in this paper. The oil pump unit is analyzed by Failure Mode and Effect Analysis (FMEA), so evaluation index can be obtained based on FMEA conclusions. The weights of different parameters in evaluation index are discussed using Analytic Hierarchy Process (AHP) with expert experience. According to the evaluation index and the weight of each parameter, the state evaluation is carried out by Fuzzy Comprehensive Evaluation (FCE) and the state is divided into five levels depending on status value, which is inspired by human body health. In order to verify the effectiveness and feasibility of the proposed method, a state evaluation of oil pump used in a pump station is taken as an example.

In the present study, extended isogeometric analysis (XIGA) is used to analyse cracks in orthotropic media. NURBS and T-splines geometric technologies are used to define the geometry and the solution. Knot insertion and order elevation are used in NURBS models, while a new local refinement algorithm is applied to T-spline models. In XIGA, the basic idea of the extended finite element method (X-FEM) is used along with isogeometric analysis for modelling discontinuities by including enrichment functions. Special orthotropic crack tip enrichments are used to reproduce the singular fields near a crack tip, and fracture properties of the models are defined by the mixed mode stress intensity factors (SIFs), which are obtained by means of the interaction integral (M-integral). Results of the proposed method are compared with other available results.

To evaluate hydrogen embrittlement, the following two types of testing method are available: (i) testing in high-pressure hydrogen gas environment and (ii) testing in ambient air using hydrogen precharged specimen. Testing in high-pressure hydrogen gas environment is technically difficult and expensive because high-pressure gas equipments, such as high-pressure vessel and pipe, have to be installed in the laboratory. On the other hand, in the case of precharging method, outgassing of hydrogen from the specimen occurs during the test. Therefore, hydrogen embrittlement can hardly be evaluated properly, especially, in long-term testing such as high cycle fatigue test at low frequency. In this study, to effectively evaluate the hydrogen embrittlement in fatigue, an experimental method, which was the four-point bending fatigue test system with a mechanism of internal circulation of hydrogen-charging solution in a pipe specimen, was developed. By using this method, the fatigue crack growth properties in the presence of hydrogen were investigated at frequencies of 0.05 Hz and 1 Hz.

In diesel generating sets, it will lead to the abominable working condition if the fault couldn't be recovered when the bolt of intercooler cracks. This paper aims at the fault of the blots of diesel generator intercooler and completes the analysis of the static strength and fatigue strength. Static intensity is checked considering blot preload and thermal stress. In order to obtain the thermal stress of the blot, thermodynamic of intercooler is calculated according to the measured temperature. Based on the measured vibration response and the finite element model, using dynamic load identification technique, equivalent excitation force of unit was solved. In order to obtain the force of bolt, the excitation force is loaded into the finite element model. By considering the thermal stress and preload as the average stress while the mechanical stress as the wave stress, fatigue strength analysis has been accomplished. Procedure of diagnosis is proposed in this paper. Finally, according to the result of intensity verification the fatigue failure is validation. Thereby, further studies are necessary to verification the result of the intensity analysis and put forward some improvement suggestion.

According to the complex process and lots of equipment, there are risks in gas compressor station. At present, research on integrity management of gas compressor station is insufficient. In this paper, the basic principle of Risk Based Inspection (RBI) and the RBI methodology are studied; the process of RBI in the gas compressor station is developed. The corrosion loop and logistics loop of the gas compressor station are determined through the study of corrosion mechanism and process of the gas compressor station. The probability of failure is calculated by using the modified coefficient, and the consequence of failure is calculated by the quantitative method. In particular, we addressed the application of a RBI methodology in a gas compressor station. The risk ranking is helpful to find the best preventive plan for inspection in the case study.

Ball bearing is widely used in a variety of machines including the transportation equipments of the automobiles and airplanes. Flaking failure is a common problem for ball bearing and it is caused by shear-mode fatigue crack growth under cyclic shear stress. Further, it is known that the premature flaking is attributed to the combined effect of hydrogen penetration into the material and cyclic shear stress during the operation. Therefore, in order to ensure the integrity of ball bearing, it is necessary to clarify the effect of hydrogen on shear-mode fatigue crack growth behavior, in particular, the threshold behavior. The evaluation of the shear-mode crack growth behavior is not easy because mode I crack branching occurs easily. Our previous studies revealed that it is required to apply static compression in the direction of specimen axis to attain a stable shear-mode fatigue crack growth. In addition, successive hydrogen supply to the specimen is essential for the evaluation of hydrogen effect on the fatigue threshold because hydrogen emits from the specimen during the fatigue test. In other words, the hydrogen-precharging method, commonly used for the research on hydrogen embrittlement, is not appropriate for the evaluation of fatigue threshold. In this study, to solve these problems, we have developed a novel, easy-to-use experimental method to evaluate the threshold behavior of shear-mode fatigue crack in the presence of hydrogen. The fundamental principle of the method is introduced in this paper.

The effects of shot peening (SP) on the torsional fatigue limit of spring steel (SUP7) were investigated for specimens with Vickers hardness values of 460, 540, and 670 HV containing a semicircular surface slit. SP was conducted on smooth specimens and specimens containing a semicircular surface slit with a depth of 0.15 or 0.3 mm. Compressive residual stress was introduced into the specimens by SP. Torsional fatigue tests were carried out under a stress ratio of R = −1. The torsional fatigue limits of the shot peened specimens with Vickers hardness values of 460, 540, and 670 HV increased by 8%–67%, 33%–143%, and 36%–127%, respectively, in comparison with the non-shot peened specimens. The maximum depth of the slit that could be rendered harmless by SP was 0.15 mm for the 460 and 670 HV specimens. However, even a slit with a depth of less than 0.15 mm could not be rendered harmless by SP for the 540 HV specimen. Considering the improvement in the torsional fatigue limit and the size of the surface defect that could be rendered harmless by SP, the 670 HV specimen is optimal for practical use.

The mechanical behavior of ductile cast iron is governed by graphite particles and casting defects in the microstructures, which can significantly decrease the fatigue strength. In our previous study, the fatigue limit of ferritic-pearlitic ductile cast iron specimens with small defects ($(\sqrt{{area}}=80\sim 1500{\rm{\mu }}{\rm{m}})$) could successfully be predicted based on the $\sqrt{{area}}$ parameter model by using $\sqrt{{area}}$ as a geometrical parameter of defect as well as the tensile strength as a material parameter. In addition, the fatigue limit for larger defects could be predicted based on the conventional fracture mechanics approach. In this study, rotating bending and tension-compression fatigue tests with ferritic-pearlitic ductile cast iron containing circumferential sharp notches as well as smooth specimens were performed to investigate quantitatively the effects of defect. The notch depths ranged 10 ∼ 2500 μm and the notch root radii were 5 and 50 μm. The stress ratios were R = −1 and 0.1. The microscopic observation of crack propagation near fatigue limit revealed that the fatigue limit was determined by the threshold condition for propagation of a small crack emanating from graphite particles. The fatigue limit could be successfully predicted as a function of R using a method proposed in this study.

Many concrete structures are deteriorating to dangerous levels throughout Japan. These concrete structures need to be inspected regularly to be sure that they are safe enough to be used. The inspection method for these concrete structures is typically the impact acoustic method. In the impact acoustic method, the worker taps the surface of the concrete with a hammer. Thus, it is necessary to set up scaffolding to access tunnel walls for inspection. Alternatively, aerial work platforms can be used. However, setting up scaffolding and aerial work platforms is not economical with regard to time or money. Therefore, we developed a testing machine using a multirotor UAV for tunnel inspection. This test machine flies by a plurality of rotors, and it is pushed along a concrete wall and moved by using rubber crawlers. The impact acoustic method is used in this testing machine. This testing machine has a hammer to make an impact, and a microphone to acquire the impact sound. The impact sound is converted into an electrical signal and is wirelessly transmitted to the computer. At the same time, the position of the testing machine is measured by image processing using a camera. The weight and dimensions of the testing machine are approximately 1.25 kg and 500 mm by 500 mm by 250 mm, respectively.

This paper presents an approach to calculate dispersion curves for homogeneous and isotropic plates subject to stress, via Semi-Analytical Finite Element and the Effective Elastic Constants, since stresses in the waveguide modify the phase and group velocities of the lamb waves. In the proposed methodology an isotropic specimen subjected to anisotropic loading is emulated by proposing an equivalent stress-free anisotropic specimen. This approximation facilitates determining the dispersion curves by using the well-studied numerical solution for the stress-free cases. The lamb wave in anisotropic materials can be studied by means of the Effective Elastic Constants, which reduces the complexity of the numerical implementation. Finally, numerical data available in literature were used to validate the proposed methodology, where it could be demonstrated its effectiveness as approximated method.

Friction plates are key components in automobile transmission system. Unfortunately, due to the tough working condition i.e. high impact, high temperature, fracture and plastic deformation are easily observed in friction plates. In order to reduce the impact load and increase the impact resistance and life span of the friction plate. This paper presents a variable damping design method and structure, by punching holes in the key position of the friction plate and filling it with damping materials, the impact load of the floating support friction plate can be controlled. Simulation is applied to study the effect of the position and number of damping holes on tooth root stress. Furthermore, physic test was designed and conducted to validate the correctness and effectiveness of the proposed method. Test result shows that the impact load of the new structure is reduced by 40% and its fatigue life is 4.7 times larger. The new structure provides a new way for floating supported friction plates design.

Assembly quality affects complex product's performance in high degree because the assembly is the end of manufacture process. In this paper, a comprehensive evaluation and forecast control of various factors affecting assembly failure is presented based on theory of gray system. Firstly, the absolute correlation degree and relative degree of correlation are calculated by using data from assembly process of complex products. Then, the comprehensive correlation degree and rank analysis are obtained with the gray method. Finally, the gray system theory is used in quality analysis and forecast control of a valve manufacturer. The final result indicates that excess amount of leakage is the main factor affecting product quality in accord with the actual situation.

The aim of this paper is the numerical prediction of the cracking path followed by a surface crack front in plates constituted of different materials (determined by the exponent m of the Paris law), subjected to cyclic tension or cyclic bending loading. To this end, a numerical modelling was developed on the basis of the discretization of the crack front (characterized with elliptical shape) and the crack advance at each point perpendicular to such a front, according to a Paris law, using the stress intensity factor (SIF) calculated by Newman and Raju. Results show that the crack leads to a preferential propagation path that corresponds to a very shallow initial crack with a quasi-circular crack front. The increase of the Paris exponent produces a quicker convergence during fatigue crack propagation from the different initial crack shapes.

The article presents the results of experimental research of the adhesive joints strength of graphite/epoxy composites and the results of the surface free energy of the composite surfaces. Two types of graphite/epoxy composites with different thickness were tested which are used to aircraft structure. The single-lap adhesive joints of epoxy composites were considered. Adhesive properties were described by surface free energy. Owens-Wendt method was used to determine surface free energy. The epoxy two-component adhesive was used to preparing the adhesive joints. Zwick/Roell 100 strength device were used to determination the shear strength of adhesive joints of epoxy composites. The strength test results showed that the highest value was obtained for adhesive joints of graphite-epoxy composite of smaller material thickness (0.48 mm). Statistical analysis of the results obtained, the study showed statistically significant differences between the values of the strength of the confidence level of 0.95. The statistical analysis of the results also showed that there are no statistical significant differences in average values of surface free energy (0.95 confidence level). It was noted that in each of the results the dispersion component of surface free energy was much greater than polar component of surface free energy.

The aim of this paper is to determine the effect of arrangement of fibreglass fabric plies in a polymer composite on adhesive joint strength. Based on the experimental results, the real effect of plies arrangement and their most favourable configuration with respect to strength is determined. The experiments were performed on 3 types of composites which had different fibre orientations. The composites had three plies of fabric. The plies arrangement in Composite I was unchanged, in Composite II the central ply had the 45° orientation, while in Composite III the outside ply (tangential to the adhesive layer) was oriented at 45°. Composite plates were first cut into smaller specimens and then adhesive-bonded in different combinations with Epidian 61/Z1/100:10 epoxy adhesive. After stabilizing, the single-lap adhesive joints were subjected to shear strength tests. It was noted that plies arrangement in composite materials affects the strength of adhesive joints made of these composites between the values of the strength of the confidence level of 0.95. The statistical analysis of the results also showed that there are no statistical significant differences in average values of surface free energy (0.95 confidence level).

1-D uniform linear array (ULA) has the shortcoming of the half-plane mirror effect, which does not allow discriminating between a target placed above the array and a target placed below the array. This paper presents time difference (TD) and multiple signal classification (MUSIC) based omni-directional impact localization on a large stiffened composite structure using improved linear array, which is able to perform omni-directional 360° localization. This array contains 2M+3 PZT sensors, where 2M+1 PZT sensors are arranged as a uniform linear array, and the other two PZT sensors are placed above and below the array. Firstly, the arrival times of impact signals observed by the other two sensors are determined using the wavelet transform. Compared with each other, the direction range of impact source can be decided in general, 0°to 180° or 180°to 360°. And then, two dimensional multiple signal classification (2D-MUSIC) based spatial spectrum formula using the uniform linear array is applied for impact localization by the general direction range. When the arrival times of impact signals observed by upper PZT is equal to that of lower PZT, the direction can be located in x axis (0°or 180°). And time difference based MUSIC method is present to locate impact position. To verify the proposed approach, the proposed approach is applied to a composite structure. The localization results are in good agreement with the actual impact occurring positions.

Among the methods of monitoring of integrity, vibration analysis is more convenient as non-destructive testing (NDT) method. Many aspects regarding the vibration monitoring of the structural integrity of damaged RC elements have not been completely analysed in literature. The correlation between the development of the crack pattern on concrete surface under bending loadings, as well as the width and depth of cracks, and the variation of dynamic parameters on a structural element is an important aspects that has to be more investigated. This paper deals with cracked RC beams controlled by NDT based on natural vibration, which may be correlated to damage degree due to cracking of concrete under severe state of loading. An experimental investigation on the assessment of RC beams in different scale under loading has been done through dynamic tests in different constraint conditions of edges measuring frequency values and frequency variation. Envelope of Frequency Response Functions (FRFs) are shown and the changes of natural frequency values are related to the damage degree of RC beams subjected to static tests. Finally, a comparison between data obtained by finite element analysis and experimental results is shown.

Dynamic loading is often an unavoidable condition in various applications of carbon-fibre-reinforced polymers and can cause various modes of damage. Realisation of dynamic damage in composites can differ significantly from that under quasi-static loading conditions. A comprehensive study of damage in composites caused by a wide variety of impact and blast loading is currently lacking. The work presents a detailed analysis of damage in specimens of a 2×2 twill weave T300 carbon-fibre/epoxy composite subjected to ballistic loading with both steel and ice projectiles (with energies from 95 J to 865 J at 70-90 m/s and 300-500 m/s, respectively) and air blast (with incident pressures of 0.4 MPa, 0.6 MPa and 0.8 MPa and wave speeds between 650 m/s and 950 m/s). The resultant damage was analysed in-depth based on detailed volumetric data obtained with high-resolution X-ray micro computed tomography.

In this paper, the similarity of the singular stress field of the single lap joint (SLJ) is discussed to evaluate the debonding fracture by the intensity of the singular stress field (ISSF). The practical method is proposed for analyzing the ISSF for the SLJ. The analysis method focuses on the FEM stress at the interface end by applying the same mesh pattern to the unknown and reference models. It is found that the independent technique useful for the bonded plate and butt joint cannot be applied to the SLJ because the singular stress field of the SLJ consists of two singular stress terms. The FEM stress is divided to two FEM stresses by applying the unknown and reference models to different minimum element sizes. Then, the practicality of the present method is examined by applying to the previous tensile test results of the SLJ composed of the aluminum alloy and the epoxy resin. The ISSFs for the SLJ were calculated by changing the adhesive thickness t₂ and the overlap length l₂. In the case of the SLJ with 225 mm in total length and 7 mm in adherend thickness, it was found that the similar singular stress fields are formed in the range of 0.15 mm ≤ t₂≤ 0.9mm and 15 mm ≤ l₂≤ 50 mm. It is shown that the critical ISSFs at the fracture are constant in the range.

Novel modulation electrical potential change (EPC) method for fatigue crack detection in a basalt fibre reinforced polymer (FRP) laminate composite pipe is carried out in this paper. The technique is applied to a laminate pipe with an embedded crack in three layers [0º/90º/0º]_s. EPC is applied for evaluating the dielectric properties of basalt FRP pipe by using an electrical capacitance sensor (ECS) to discern damages in the pipe. Twelve electrodes are mounted on the outer surface of the pipe and the changes in the modulation dielectric properties of the piping system are analyzed to detect damages in the pipe. An embedded crack is created by a fatigue internal pressure test. The capacitance values, capacitance change and node potential distribution of ECS electrodes are calculated before and after crack initiates using a finite element method (FEM) by ANSYS and MATLAB, which are combined to simulate sensor characteristics and fatigue behaviour. The crack lengths of the basalt FRP are investigated for various number of cycles to failure for determining crack growth rate. Response surfaces are adopted as a tool for solving inverse problems to estimate crack lengths from the measured electric potential differences of all segments between electrodes to validate the FEM results. The results show that, the good convergence between the FEM and estimated results. Also the results of this study show that the electrical potential difference of the basalt FRP laminate increases during cyclic loading, caused by matrix cracking. The results indicate that the proposed method successfully provides fatigue crack detection for basalt FRP laminate composite pipes.

The inclined bimaterial interface crack problem is studied from theoretical and computational aspects. The original problem is transformed into an eigen value problem by using the symplectic approach, and the eigen solution are obtained. A Symplectic Analytical Singular Element (SASE), of which the interior fields are described by the obtained eigen solutions, is developed. The stress intensity factors (SIFs) can be calculated directly without any post-processing. Numerical example on a square bimaterial plate containing an inclined crack is provided to validate the proposed method. The comparison of the predicted results with the existing result indicates that the proposed method is accurate for the modelling of the inclined bimaterial interface crack.

Acoustic emission based damage detection in composite structures is based on detection of ultra high frequency packets of acoustic waves emitted from damage sources (such as fibre breakage, fatigue fracture, amongst others) with a network of distributed sensors. This non-destructive monitoring scheme requires solving an inverse problem where the measured signals are linked back to the location of the source. This in turn enables rapid deployment of mitigative measures. The presence of significant amount of uncertainty associated with the operating conditions and measurements makes the problem of damage identification quite challenging. The uncertainties stem from the fact that the measured signals are affected by the irregular geometries, manufacturing imprecision, imperfect boundary conditions, existing damages/structural degradation, amongst others. This work aims to tackle these uncertainties within a framework of automated probabilistic damage detection. The method trains a probabilistic model of the parametrized input and output model of the acoustic emission system with experimental data to give probabilistic descriptors of damage locations. A response surface modelling the acoustic emission as a function of parametrized damage signals collected from sensors would be calibrated with a training dataset using Bayesian inference. This is used to deduce damage locations in the online monitoring phase. During online monitoring, the spatially correlated time data is utilized in conjunction with the calibrated acoustic emissions model to infer the probabilistic description of the acoustic emission source within a hierarchical Bayesian inference framework. The methodology is tested on a composite structure consisting of carbon fibre panel with stiffeners and damage source behaviour has been experimentally simulated using standard H-N sources. The methodology presented in this study would be applicable in the current form to structural damage detection under varying operational loads and would be investigated in future studies.

This study presents a two-stage approach based on residual force vector and response sensitivity analysis for structural damage identification in axially functionally graded (AFG) beams. The local damage is simulated by a reduction in the elemental Young's modulus of the beam. The residual force vector is used to find the suspicious damaged elements in the beam at first. Then, a hybrid objective function is established and a sensitivity-based model updating method is adopted to identify the perturbation of the stiffness parameter from the measured acceleration responses. Two numerical examples are investigated to illustrate the correctness and efficiency of the proposed method. The effects of measurement noise on the identification results are investigated. Studies in this paper indicate that the proposed method is efficient and robust for identifying damages in the axially functionally graded beams. The advantage of the present approach lies in that only a few number of acceleration measurements and the first several natural frequencies of the beam are needed in the identification.

Compared with riveted and welded joints, bolted joints have advantages of easily dismantled, high load carrying and load-transferring capacity. However, bolted joints are also weaker components of assembled structures. Structural damage detection (SDD) on bolted joints is much required in the field of structural health monitoring (SHM). A new SDD method is proposed for damage identification of structures with bolted joints based on residual error of AR model in time series analysis. Firstly, a new data standardization process is defined to maintain the information of damage location. Then, a new structural damage feature sensitive to structural damage is developed based on the standard deviation of AR model residual errors. To verify the proposed method, a bolted joint structure is designed and fabricated in laboratory, connection damages of structures are simulated by loosening the bolted joints. The acceleration responses of structures with bolted joints under healthy and damage cases are acquired. Finally, the SDD is performed by traditional DSF and the new DSF. The illustrated results show that the proposed method is a hybrid tool for the bolted joint damage detection with the new damage-sensitive feature. In addition, some related issues will be discussed as well.

The delamination problem is very important failure mechanism in certain types of composite structures. Detecting this type of damage using vibration data is currently a problem of interest to the structural health monitoring community. In this paper, we used finite element method with embedded interface for analysing damaged laminated composite structures. The flexibly modal method, in which analysis data is related to finite element modelling, is used to detect and localize delamination. Several numerical examples are presented in order to evaluate the accuracy this approach.

In this paper, a suitable and simple computational formulation based on Isogeometric Analysis (IGA) integrated with higher-order shear deformation theory (HSDT) is introduced for size-dependent buckling analysis of functionally graded material (FGM) nanoplates. The material properties of FGM based on the Mori–Tanaka schemes and the rule of mixture are used. The differential nonlocal equations are utilized to take into account size effects. The nonlocal governing equations are approximated according to IGA based on HSDT, which satisfies naturally the higher-order derivatives continuity requirement in weak form of FGM nanoplates. The effect of nonlocal approach on the behaviors of the FGM nanoplates with several volume fraction exponents is investigated to show the reliability of the proposed method.