Table of contents

Cone-beam x-ray computed tomography (XCT) is a radiographic scanning technique that allows the non-destructive dimensional measurement of an object's internal and external features. XCT measurements are influenced by a number of different factors that are poorly understood. This work investigates how non-linear x-ray attenuation caused by beam hardening and scatter influences XCT-based dimensional measurements through the use of simulated data. For the measurement task considered, both scatter and beam hardening are found to influence dimensional measurements when evaluated using the ISO50 surface determination method. On the other hand, only beam hardening is found to influence dimensional measurements when evaluated using an advanced surface determination method. Based on the results presented, recommendations on the use of beam hardening and scatter correction for dimensional XCT are given.

Measurement uncertainty in meteorology has been addressed in a number of recent projects. In urban environments, uncertainty is also affected by local effects which are more difficult to deal with than for synoptic stations. In Italy, beginning in 2010, an urban meteorological network (Climate Network^®) was designed, set up and managed at national level according to high metrological standards and homogeneity criteria to support energy applications. The availability of such a high-quality operative automatic weather station network represents an opportunity to investigate the effects of station siting and sensor exposure and to estimate the related measurement uncertainty. An extended metadata set was established for the stations in Milan, including siting and exposure details. Statistical analysis on an almost 3-year-long operational period assessed network homogeneity, quality and reliability. Deviations from reference mean values were then evaluated in selected low-gradient local weather situations in order to investigate siting and exposure effects. In this paper the methodology is depicted and preliminary results of its application to air temperature discussed; this allowed the setting of an upper limit of 1 °C for the added measurement uncertainty at the top of the urban canopy layer.

The Dimensional Metrology Group at the National Institute of Standards and Technology is performing research to support the development of documentary standards within the ASTM E57 committee. This committee is addressing the point-to-point performance evaluation of a subclass of 3D imaging systems called terrestrial laser scanners (TLSs), which are laser-based and use a spherical coordinate system. This paper discusses the usage of sphere targets for this effort, and methods to minimize the errors due to the determination of their centers. The key contributions of this paper include methods to segment sphere data from a TLS point cloud, and the study of some of the factors that influence the determination of sphere centers.

Stacked objects volume measurement is now widely used in the fields of enterprise material management. It is significant to improve the efficiency of enterprise management and to reduce the cost of management and operation. The method based on laser sensing is one of the key methods to measure the stacked objects volume. This paper presents a laser sensing measurement method of stacked objects based on bottom plane extraction and real-time calibration. A calibration method for a laser scanning sensor and inertial measurement sensor is proposed. Three-dimensional reconstructions of stacked objects and volume calculations are carried out after acquisition and processing of point clouds. Volume measurement experiments of the single box and stacked boxes have been conducted respectively. Experimental results show that the measurement method is feasible and valid with good accuracy.

In this paper, a new variational Bayesian adaptive cubature Kalman filter (VBACKF) is proposed for nonlinear state estimation. Although the conventional VBACKF performs better than cubature Kalman filtering (CKF) in solving nonlinear systems with time-varying measurement noise, its performance may degrade due to the uncertainty of the system model. To overcome this drawback, a multilayer feed-forward neural network (MFNN) is used to aid the conventional VBACKF, generalizing it to attain higher estimation accuracy and robustness. In the proposed neural-network-aided variational Bayesian adaptive cubature Kalman filter (NN-VBACKF), the MFNN is used to turn the state estimation of the VBACKF adaptively, and it is used for both state estimation and in the online training paradigm simultaneously. To evaluate the performance of the proposed method, it is compared with CKF and VBACKF via target tracking problems. The simulation results demonstrate that the estimation accuracy and robustness of the proposed method are better than those of the CKF and VBACKF.

In this paper, a four-probe measurement system is implemented and verified for the carriage slide motion error measurement of a large-scale roll lathe used in hybrid manufacturing where a laser machining probe and a diamond cutting tool are placed on two sides of a roll workpiece for manufacturing. The motion error of the carriage slide of the roll lathe is composed of two straightness motion error components and two parallelism motion error components in the vertical and horizontal planes. Four displacement measurement probes, which are mounted on the carriage slide with respect to four opposing sides of the roll workpiece, are employed for the measurement. Firstly, based on the reversal technique, the four probes are moved by the carriage slide to scan the roll workpiece before and after a 180-degree rotation of the roll workpiece. Taking into consideration the fact that the machining accuracy of the lathe is influenced by not only the carriage slide motion error but also the gravity deformation of the large-scale roll workpiece due to its heavy weight, the vertical motion error is thus characterized relating to the deformed axis of the roll workpiece. The horizontal straightness motion error can also be synchronously obtained based on the reversal technique. In addition, based on an error separation algorithm, the vertical and horizontal parallelism motion error components are identified by scanning the rotating roll workpiece at the start and the end positions of the carriage slide, respectively. The feasibility and reliability of the proposed motion error measurement system are demonstrated by the experimental results and the measurement uncertainty analysis.

With the aim of reducing sampling density while having minimal impact on surface reconstruction accuracy, an adaptive sampling method based on Gaussian process inference is proposed. In each iterative step, the current sampling points serve as the training data to predict surface topography and then a new sampling point is adaptively located and inserted at the position where the maximum inference uncertainty is estimated. The updated samples are trained in the next step. By such an iterative training–inference–sampling approach, the reconstructed topography can converge to the expected one efficiently. Demonstrations on different structured, freeform and roughness surfaces ascertain the effectiveness of the sampling strategy. It can lead to an accurate inference of the surface topography and a sufficient reduction of data points compared with conventional uniform sampling. Robustness against random surface features, measurement noise and sharp height changes is further discussed. Such an adaptive sampling method is extremely suitable for discrete point-by-point measurements.

Doppler distortion and background noise can reduce the effectiveness of wayside acoustic train bearing monitoring and fault diagnosis. This paper proposes a method of combining a microphone array and matching pursuit algorithm to overcome these difficulties. First, a dictionary is constructed based on the characteristics and mechanism of a far-field assumption. Then, the angle of arrival of the train bearing is acquired when applying matching pursuit to analyze the acoustic array signals. Finally, after obtaining the resampling time series, the Doppler distortion can be corrected, which is convenient for further diagnostic work. Compared with traditional single-microphone Doppler correction methods, the advantages of the presented array method are its robustness to background noise and its barely requiring pre-measuring parameters. Simulation and experimental study show that the proposed method is effective in performing wayside acoustic bearing fault diagnosis.

Digital volume correlation (DVC) is a powerful technique for quantifying interior deformation within solid opaque materials and biological tissues. In the last two decades, great efforts have been made to improve the accuracy and efficiency of the DVC algorithm. However, there is still a lack of a flexible, robust and accurate version that can be efficiently implemented in personal computers with limited RAM. This paper proposes an advanced DVC method that can realize accurate full-field internal deformation measurement applicable to high-resolution volume images with up to billions of voxels. Specifically, a novel layer-wise reliability-guided displacement tracking strategy combined with dynamic data management is presented to guide the DVC computation from slice to slice. The displacements at specified calculation points in each layer are computed using the advanced 3D inverse-compositional Gauss–Newton algorithm with the complete initial guess of the deformation vector accurately predicted from the computed calculation points. Since only limited slices of interest in the reference and deformed volume images rather than the whole volume images are required, the DVC calculation can thus be efficiently implemented on personal computers. The flexibility, accuracy and efficiency of the presented DVC approach are demonstrated by analyzing computer-simulated and experimentally obtained high-resolution volume images.

Software for the evaluation of areal surface texture function parameters is described. Definitions of the parameters, expressed in terms of the inverse areal material ratio function, are provided along with details of the numerical algorithms employed in the software to implement calculations to evaluate approximations to the parameters according to those definitions. Results obtained using the software to process a number of data sets representing different surfaces are compared with those returned by proprietary software for surface texture measurement. Differences in the results, arising from different choices being made when implementing the steps in the parameter evaluation process, are discussed.

Micro-capacitance sensors are widely applied in industrial applications for the measurement of mechanical variations. The measurement accuracy of micro-capacitance sensors is highly dependent on the capacitance measurement circuit. To overcome the inability of commonly used methods to directly measure capacitance variation and deal with the conflict between the measurement range and accuracy, this paper presents a capacitance variation measurement method which is able to measure the output capacitance variation (relative value) of the micro-capacitance sensor with a continuously variable measuring range. We present the principles and analyze the non-ideal factors affecting this method. To implement the method, we developed a capacitance variation measurement circuit and carried out experiments to test the circuit. The result shows that the circuit is able to measure a capacitance variation range of 0–700 pF linearly with a maximum relative accuracy of 0.05% and a capacitance range of 0–2 nF (with a baseline capacitance of 1 nF) with a constant resolution of 0.03%. The circuit is proposed as a new method to measure capacitance and is expected to have applications in micro-capacitance sensors for measuring capacitance variation with a continuously variable measuring range.

The present paper develops a series of methods for the estimation of uncertainty when measuring certain measurands of interest in surveying practice, such as points elevation given a planimetric position within a triangle mesh, 2D and 3D lengths (including perimeters enclosures), 2D areas (horizontal surfaces) and 3D areas (natural surfaces). The basis for the proposed methodology is the law of propagation of variance–covariance, which, applied to the corresponding model for each measurand, allows calculating the resulting uncertainty from known measurement errors. The methods are tested first in a small example, with a limited number of measurement points, and then in two real-life measurements.

In addition, the proposed methods have been incorporated to commercial software used in the field of surveying engineering and focused on the creation of digital terrain models. The aim of this evolution is, firstly, to comply with the guidelines of the BIPM (Bureau International des Poids et Mesures), as the international reference agency in the field of metrology, in relation to the determination and expression of uncertainty; and secondly, to improve the quality of the measurement by indicating the uncertainty associated with a given level of confidence. The conceptual and mathematical developments for the uncertainty estimation in the aforementioned cases were conducted by researchers from the AssIST group at the University of Oviedo, eventually resulting in several different mathematical algorithms implemented in the form of MATLAB code. Based on these prototypes, technicians incorporated the referred functionality to commercial software, developed in C++. As a result of this collaboration, in early 2016 a new version of this commercial software was made available, which will be the first, as far as the authors are aware, that incorporates the possibility of estimating the uncertainty for a given level of confidence when computing the aforementioned surveying measurands.

The photopyroelectric (PPE) technique in the front configuration consists in illuminating one surface of a pyroelectric slab while the other surface is in contact with the test sample. This method has been widely used to measure the thermal effusivity of liquids. Recently, it has been extended to measure the thermal effusivity of solids, by taking into account the influence of the coupling fluid layer used to guarantee the thermal contact. In both cases, the sample (liquid or solid) must be very thick. In this work, we propose a classical frequency scan of a thin sample slab to retrieve the thermal diffusivity and effusivity simultaneously. We use the amplitude and the phase of the front PPE signal, which depend on four parameters: the sample diffusivity and effusivity, the coupling fluid thickness and the coefficient of heat losses. It is demonstrated that the four quantities are not correlated. PPE measurements performed on a set of calibrated solids confirm the ability of the method to obtain the thermal diffusivity and effusivity of solids accurately.

Registration of multiple sensors is a basic step in multi-sensor dimensional or coordinate measuring systems before any measurement. In most cases, a common standard is used to be measured by all sensors, and this may work well for general registration of multiple homogeneous sensors. However, when inhomogeneous sensors detect a common standard, it is usually very difficult to obtain the same information, because of the different working principles of the sensors. In this paper, a new method called multiple steps registration is proposed to register two sensors: a video camera sensor (VCS) and a tactile probe sensor (TPS). In this method, the two sensors measure two separated standards: a chrome circle on a reticle and a reference sphere with a constant distance between them, fixed on a steel plate. The VCS captures only the circle and the TPS touches only the sphere. Both simulations and real experiments demonstrate that the proposed method is robust and accurate in the registration of multiple inhomogeneous sensors in a dimensional measurement system.

The calibration of the angle encoder is necessary to improve the accuracy of angle measurement in precision rotating devices. Due to the characteristics of in situ calibration of encoders, self-calibration methods depending on special arrangements of multiple scanning heads have been widely used. Conventional works usually arrange the scanning heads in a regularly distributed way, generally involving too many scanning heads, especially when more high order Fourier components of the encoder error are calibrated. This paper presents an optimization-based arrangement method for self-calibration of angle encoders. Fourier approaches are used to determine the error of encoder from the angle differences measured between scanning heads. The relations between detectable Fourier components of the error and angular intervals of the heads are obtained from the properties of transfer functions. The optimal arrangements for two and three scanning heads, including the adjustment tolerances of the heads with the range of tested Fourier orders, are presented. The results of simulations and experiments demonstrate that the proposed optimal schemes can realize the same performance of calibration but with fewer scanning heads, compared to the conventional methods.

Measurement of the complex permittivity (CP) of a material at different temperatures in microwave heating applications is difficult and complicated. In this paper a simple and convenient method is employed to measure the CP of a material over variable temperature. In this method the temperature of a sample is increased experimentally to obtain the formula for the relationship between CP and temperature by a genetic algorithm. We chose agar solution (sample) and a Yangshao reactor (microwave heating system) to validate the reliability and feasibility of this method. The physical parameters (the heat capacity, C_p, density, ρ, and thermal conductivity, k) of the sample are set as constants in the process of simulation and inversion. We analyze the influence of the variation of physical parameters with temperature on the accuracy of the inversion results. It is demonstrated that the variation of these physical parameters has little effect on the inversion results in a certain temperature range.

Metering performance is the key parameter of an electronic voltage transformer (EVT), and it requires high accuracy. The conventional off-line calibration method using a standard voltage transformer is not suitable for the key equipment in a smart substation, which needs on-line monitoring. In this article, we propose a method for monitoring the metering performance of an EVT on-line based on cyber-physics correlation analysis. By the electrical and physical properties of a substation running in three-phase symmetry, the principal component analysis method is used to separate the metering deviation caused by the primary fluctuation and the EVT anomaly. The characteristic statistics of the measured data during operation are extracted, and the metering performance of the EVT is evaluated by analyzing the change in statistics. The experimental results show that the method successfully monitors the metering deviation of a Class 0.2 EVT accurately. The method demonstrates the accurate evaluation of on-line monitoring of the metering performance on an EVT without a standard voltage transformer.

Localisation of axial peaks is essential for height determination in confocal microscopy. Several algorithms have been proposed for reliable height extraction in surface topography measurements. However, most of these algorithms use nonlinear processing, which precludes estimating the peak height uncertainty. A Monte Carlo based standard uncertainty analysis model is developed here to evaluate the precision of height extraction algorithms. The key parameters of this model are the vertical sampling deviation and the size of the scanning pitch. Height extraction uncertainty of the centroid algorithm and nonlinear fitting algorithms were calculated using simulations. Our results offer a reference for selecting algorithms for confocal metrology.

Today, the quantitative evaluation of the quality of circular or cylindrical workpieces is becoming increasingly important for the relevant industrial production sectors. Although there are already some roundness deviation evaluation algorithms available to accomplish this task, these methods are always done in a holistic way. In many industrial scenarios, however, fine evaluation of the roundness variation of local segments is often more practical than the global assessment. By performing a fine evaluation of roundness variation of local segments, crucial information that can reveal intrinsic quality characteristics of both the workpiece and the production machine can be retrieved. However, this important issue has not been well studied. To deal with this problem, a roundness deviation evaluation method based on statistical analysis of local least square circles was proposed. Experimental results illustrated that the proposed method can stably and reliably evaluate the local and global roundness deviations effectively.

Micro-electro-mechanical systems (MEMS) inertial measurement devices tend to be widely used in inertial navigation systems and have quickly emerged on the market due to their characteristics of low cost, high reliability and small size. Calibration is the most effective way to remove the deterministic error of an inertial reference unit (IRU), which in this paper consists of three orthogonally mounted MEMS gyros. However, common testing methods in the lab cannot predict the corresponding errors precisely when the turntable's working condition is restricted. In this paper, the turntable can only provide a relatively small rotation angle. Moreover, the errors must be compensated exactly because of the great effect caused by the high angular velocity of the craft. To deal with this question, a new method is proposed to evaluate the MEMS IRU's performance. In the calibration procedure, a one-axis table that can rotate a limited angle in the form of a sine function is utilized to provide the MEMS IRU's angular velocity. A new algorithm based on Fourier series is designed to calculate the misalignment and scale factor errors. The proposed method is tested in a set of experiments, and the calibration results are compared to a traditional calibration method performed under normal working conditions to verify their correctness. In addition, a verification test in the given rotation speed is implemented for further demonstration.

We report a highly sensitive strain sensor with low temperature sensitivity based on the fiber loop ringdown technique. An innovative approach that employs a micro air-gap as the strain sensor head is described. The sensor has demonstrated the static strain sensitivity of 0.26 µs/µε, corresponding to the detection limit of 65 nε with the low temperature cross sensitivity of 37 nε/°C. This is the highest static strain sensitivity achieved without using a combination of fiber optic sensing components, such as fiber Bragg gratings or Fabry–Perot interferometers. Moreover, the sensor design allows the strain sensitivity and measuring range to be adjusted by changing the length of the sensor.

In this paper we propose and experimentally demonstrate an optical fiber structure sensor based on a Mach–Zehnder interferometer for pressure measurement. The fiber sensor is composed of a single-mode-no-core-single-mode structure, a section of capillary pure silica tube and refractive index matching fluid (RIMF). As the pressure decreases, the sealed air in the tube expands and the liquid level of the RIMF increases, which causes a wavelength shift of the interferometer. The measurement of the pressure variation can thus be achieved by monitoring the wavelength shift. The experimental results agree well with the numerical simulation, and a maximum pressure sensitivity of 266.6 nm ${\rm Mpa}^{-1}$ is achieved experimentally. Furthermore, the proposed fiber sensor has the potential to obtain higher sensitivity by enlarging the length of the air cavity.

Plastic optical fiber (POF) sensors have shown excellent potential for damage detection and structural health monitoring in a variety of engineering structures. This paper discusses the feasibility of using POF sensors in conjunction with a signal-processing algorithm capable of detecting and monitoring fatigue-induced cracks in train track steel structures in real time. The POF sensor, which was modified from an existing design to increase the signal sensitivity, allows for accurate detection of a fatigue crack developed in a specimen, and was found to compare well to the reference acoustic emission (AE) sensors and crack opening displacement (COD) gauge attached to the specimen. The crack-detection technique, which relies on capturing the intensity variation of the POF sensor, was not susceptible to any signal fluctuations commonly associated with intensity-based optical fiber sensors. The results show that the technique has potential for use in detecting the initiation and propagation of specific segments of a structure vulnerable to cracking due to external cyclic loading, e.g. at welded joints in train tracks under train loads or offshore structures subject to wave loads. The POF sensor system is composed of inexpensive parts (LED light source, photodetectors, and data acquisition units) and can easily be installed to the host structure. To validate the proposed damage-detection technique, the instrumented specimens are subjected to cyclic loading in order to induce stable crack propagation in the specimen. A COD gauge and AE were used for the purpose of calibration and comparison. The results show remarkable resemblance in terms of crack initiation and propagation identification exhibited by all three types of sensors, highlighting the potential of the proposed sensor for crack initiation detection and subsequent monitoring of crack propagation.

An over-constrained, parallel six-dimensional force sensor has various advantages, including its ability to bear heavy loads and provide redundant force measurement information. These advantages render the sensor valuable in important applications in the field of aerospace (space docking tests, etc). The stiffness of each component in the over-constrained structure has a considerable influence on the internal force distribution of the structure. Thus, the measurement model changes when the measurement branches of the sensor are under tensile or compressive force. This study establishes a general measurement model for an over-constrained parallel six-dimensional force sensor considering the different branch tensions and compression stiffness values. Numerical calculations and analyses are performed using practical examples. Based on the parallel mechanism, an over-constrained, orthogonal structure is proposed for a six-dimensional force sensor. Hence, a prototype is designed and developed, and a calibration experiment is conducted. The measurement accuracy of the sensor is improved based on the measurement model under different branch tensions and compression stiffness values. Moreover, the largest class I error is reduced from 5.81 to 2.23% full scale (FS), and the largest class II error is reduced from 3.425 to 1.871% FS.

Small scale flow phenomena play an important role across engineering, biological and chemical sciences. To gain deeper understanding of the influence of those flow phenomena involved, measurement techniques with high spatial resolution are often required, presuming a calibration of very low uncertainty. To enable such measurements, a method for the in situ calibration of an interferometric flow velocity profile sensor is presented. This sensor, with demonstrated spatial resolution better than 1 μm, allows for spatially-resolving measurements with low velocity uncertainty in flows with high velocity gradients, on condition that the spatial behavior of the interference fringe systems is well-known by calibration with low uncertainty, especially challenging to obtain at applications with geometries difficult to access. The calibration method described herein uses three interfering beams to form the interference fringe systems of the sensor, yielding Doppler burst signals exhibiting two peaks in the frequency domain whose amplitude ratio varies periodically along the measurement volume major z-axis, giving a further independent value of the axial tracer particle position that can be used to determine the calibration functions of the sensor during the flow measurement. A flow measurement in a microchannel experimentally validates that the presented approach allows for simultaneously estimating the calibration functions and the velocity profile, providing flow measurements with very low systematic measurement errors of the particle position of less than 400 nm (confidence interval 95%). In that way, the interferometric flow velocity profile sensor utilizing the in situ self-calibration method promises valuable insights on small scale flow phenomena, such as those given in shear and boundary layer flows, by featuring reliable flow measurements due to minimum systematic and statistical measurement errors.

Femtosecond optical frequency combs (FOFCs) make it possible to measure the absolute frequency of a laser, which greatly simplifies quantity traceability and comparison of the absolute frequency. In order to ensure the accuracy and reliability of the measurement, the signal-to-noise ratio (SNR) of the beat note (f_b) between an FOFC and a laser should be above 30 dB. In this paper, an Er-doped FOFC (Er-FOFC) is employed, at a repetition rate of 305 MHz. The spectral intensity near the 1 µm wavelength in an octave-spanning supercontinuum generated from the Er-FOFC is enhanced effectively by cascading an Yb-doped fiber amplifier after spectral broadening, which helps improve the SNR of the beat note between the comb light and an iodine-stabilized 532 nm laser. This method can effectively reduce the intensity requirements on the 1 µm wavelength when the spectrum is directly broadened in an Er-FOFC.

Dynamic measurement of rail wear using a laser imaging system suffers from random vibrations in the laser-based imaging sensor which cause distorted rail profiles. In this paper, a simple and effective method for rectifying profile deviation is presented to address this issue. There are two main steps: profile recognition and distortion calibration. According to the constant camera and projector parameters, efficient recognition of measured profiles is achieved by analyzing the geometric difference between normal profiles and distorted ones. For a distorted profile, by constructing coordinate sets projecting from it to the standard one on triple projecting primitives, including the rail head inner line, rail waist curve and rail jaw, iterative extrinsic camera parameter self-compensation is implemented. The distortion is calibrated by projecting the distorted profile onto the x–y plane of a measuring coordinate frame, which is parallel to the rail cross section, to eliminate the influence of random vibrations in the laser-based imaging sensor. As well as evaluating the implementation with comprehensive experiments, we also compare our method with other published works. The results exhibit the effectiveness and superiority of our method for the dynamic measurement of rail wear.

A novel roll angular displacement measurement method based on acousto-optic modulators (AOMs) is presented, where the AOMs are adopted to reduce the frequency-difference to overcome the phase fluctuation. The novel method improves the resolution and simplifies the system configuration by reducing the optical components in the measuring light path. A mathematical model is established, and the impacts of the optical components' error on measurement errors and magnification are analyzed in detail based on the model. The analysis results can then be used to optimize the system configuration. Experiments are carried out to validate the presented method, which show that a resolution of 0.016 arcsec has eventually been achieved.

Eddy current flow meters are widely used for measuring the flow velocity of electrically conducting fluids. Since the flow induced perturbations of a magnetic field depend both on the geometry and the conductivity of the fluid, extensive calibration is needed to get accurate results. Transient eddy current flow metering has been developed to overcome this problem. It relies on tracking the position of an impressed eddy current system that is moving with the same velocity as the conductive fluid. We present an immersed version of this measurement technique and demonstrate its viability by numerical simulations and a first experimental validation.

The focus measure is widely used in the shape from focus, passive autofocus, etc, and its performance determines the application results of these techniques. In this paper, a new focus measure that combines two existing focus measures is proposed to improve performance, including the sensitivity to defocus and the independence of image content. Comparative experiments are conducted to verify the effectiveness of the proposed focus measure. This paper provides a new idea for follow-up research on high-performance focus measures.

In recent years, many efforts have been made to exploit full-field measurement optical techniques for modal identification. Three-dimensional digital image correlation using high-speed cameras has been extensively employed for this purpose. Modal identification algorithms are applied to process the frequency response functions (FRF), which relate the displacement response of the structure to the excitation force. However, one of the most common tests for modal analysis involves the base motion excitation of a structural element instead of force excitation. In this case, the relationship between response and excitation is typically based on displacements, which are known as transmissibility functions. In this study, a methodology for experimental modal analysis using high-speed 3D digital image correlation and base motion excitation tests is proposed. In particular, a cantilever beam was excited from its base with a random signal, using a clamped edge join. Full-field transmissibility functions were obtained through the beam and converted into FRF for proper identification, considering a single degree-of-freedom theoretical conversion. Subsequently, modal identification was performed using a circle-fit approach. The proposed methodology facilitates the management of the typically large amounts of data points involved in the DIC measurement during modal identification. Moreover, it was possible to determine the natural frequencies, damping ratios and full-field mode shapes without requiring any additional tests. Finally, the results were experimentally validated by comparing them with those obtained by employing traditional accelerometers, analytical models and finite element method analyses. The comparison was performed by using the quantitative indicator modal assurance criterion. The results showed a high level of correspondence, consolidating the proposed experimental methodology.

Infrared thermography is widely used in non-destructive testing and in the non-destructive evaluation of subsurface defects in several materials. The detection and reconstruction (location and shape) of a defect inside a material from thermal data requires the solution of an inverse heat conduction problem. Here the problem is tackled by the thin-plate approximation of the investigated domain. A number of physical quantities must be known for the reconstruction procedure to be successful: some relating to the material (thermal conductivity, heat capacity, density), usually known, and others relating to the heating process. This paper proposes procedures for accurately measuring the latter, whose importance is often not given due consideration. Those procedures allow us to accurately measure the heat flux distribution produced by the sources on the heated surface, and the heat exchange coefficient at the remaining surfaces, and are easily applicable in 'on field' situations.

The presence of carbon atoms in silicon carbide and diamond makes these materials ideal candidates for direct fast neutron detectors. Furthermore the low atomic number, strong covalent bonds, high displacement energies, wide bandgap and low intrinsic carrier concentrations make these semiconductor detectors potentially suitable for applications where rugged, high-temperature, low-gamma-sensitivity detectors are required, such as active interrogation, electronic personal neutron dosimetry and harsh environment detectors.

A thorough direct performance comparison of the detection capabilities of semi-insulating silicon carbide (SiC–SI), single crystal diamond (D–SC), polycrystalline diamond (D–PC) and a self-biased epitaxial silicon carbide (SiC–EP) detector has been conducted and benchmarked against a commercial silicon PIN (Si–PIN) diode, in a wide range of alpha (Am-241), beta (Sr/Y-90), ionizing photon (65 keV to 1332 keV) and neutron radiation fields (including 1.2 MeV to 16.5 MeV mono-energetic neutrons, as well as neutrons from AmBe and Cf-252 sources).

All detectors were shown to be able to directly detect and distinguish both the different radiation types and energies by using a simple energy threshold discrimination method. The SiC devices demonstrated the best neutron energy discrimination ratio ($E_{\max}$($n=5$ MeV)/$E_{\max}$($n=1$ MeV)  ≈5), whereas a superior neutron/photon cross-sensitivity ratio was observed in the D–PC detector ($E_{\max}$(AmBe)/$E_{\max}$(Co-60)  ≈16). Further work also demonstrated that the cross-sensitivity ratios can be improved through use of a simple proton-recoil conversion layer.

Stability issues were also observed in the D–SC, D–PC and SiC–SI detectors while under irradiation, namely a change of energy peak position and/or count rate with time (often referred to as the polarization effect). This phenomenon within the detectors was non-debilitating over the time period tested ($>$5 h) and, as such, stable operation was possible.

Furthermore, the D–SC, self-biased SiC–EP and semi-insulating SiC detectors were shown to operate over the temperature range $-60$ °C to $+100$ °C.

In the present paper, the authors discussed the functioning of their own analyzer for measuring gas contained in the pore space of high strength rocks. A sample is placed inside a hermetic measuring chamber, and then undergoes impact milling as a result of colliding with the vibrating blade of a knife which is rotationally driven by a high-speed brushless electric motor. The measuring chamber is equipped with all the necessary sensors, i.e. gas, pressure, and temperature sensors. Trial tests involving the comminution of dolomite and anhydrite samples demonstrated that the constructed device is able to break up rocks into grains so fine that they are measured in single microns, and the sensors used in the construction ensure balancing of the released gas. The tests of the analyzer showed that the metrological concept behind it, together with the way it was built, make it fit for measurements of the content and composition of selected gases from the rock pore space. On the basis of the conducted tests of balancing the gases contained in the two samples, it was stated that the gas content of Sample no. 1 was (0.055  ±  0.002) cm³ g⁻¹, and Sample no. 2 contained gas at atmospheric pressure, composed mostly of air.

A plug flow reactor (PFR) is built for investigating the oxidation chemistry of fuels at up to 50 bar and 1000 K. These conditions include those corresponding to the low temperature combustion (i.e. the autoignition) that commonly occurs in internal combustion engines. Turbulent flow that approximates ideal, plug flow conditions is established in a quartz tube reactor. The reacting mixture is highly diluted by excess air to reduce the reaction rates for kinetic investigations. A novel mixer design is used to achieve fast mixing of the preheated air and fuel vapour at the reactor entrance, reducing the issue of reaction initialization in kinetic modelling. A water-cooled probe moves along the reactor extracting gases for further analysis. Measurement of the sampled gas temperature uses an extended form of a three-thermocouple method that corrects for radiative heat losses from the thermocouples to the enclosed PFR environment.

Investigation of the PFR's operation is first conducted using non-reacting flows, and then with isooctane oxidation at 900 K and 10 bar. Mixing of the non-reacting temperature and species fields is shown to be rapid. The measured fuel consumption and CO formation are then closely reproduced by kinetic modelling using an extensively validated iso-octane mechanism from the literature and the corrected gas temperature. Together, these results demonstrate the PFR's utility for chemical kinetic investigations.

State-of-the-art multisensory technologies and heterogeneous sensor networks propose a wide range of response measurement opportunities for structural health monitoring (SHM). Measuring and fusing different physical quantities in terms of structural vibrations can provide alternative acquisition methods and improve the quality of the modal testing results. In this study, a recently introduced SHM concept, SHM with smartphones, is focused to utilize multisensory smartphone features for a hybridized structural vibration response measurement framework. Based on vibration testing of a small-scale multistory laboratory model, displacement and acceleration responses are monitored using two different smartphone sensors, an embedded camera and accelerometer, respectively. Double-integration or differentiation among different measurement types is performed to combine multisensory measurements on a comparative basis. In addition, distributed sensor signals from collocated devices are processed for modal identification, and performance of smartphone-based sensing platforms are tested under different configuration scenarios and heterogeneity levels. The results of these tests show a novel and successful implementation of a hybrid motion sensing platform through multiple sensor type and device integration. Despite the heterogeneity of motion data obtained from different smartphone devices and technologies, it is shown that multisensory response measurements can be blended for experimental modal analysis. Getting benefit from the accessibility of smartphone technology, similar smartphone-based dynamic testing methodologies can provide innovative SHM solutions with mobile, programmable, and cost-free interfaces.

Optical scanners play a key role in many three-dimensional (3D) printing and CAD/CAM applications. However, existing optical scanners are generally designed to provide either a wide scanning area or a high 3D reconstruction accuracy from a lens with a fixed focal length. In the former case, the scanning area is increased at the expense of the reconstruction accuracy, while in the latter case, the reconstruction performance is improved at the expense of a more limited scanning range. In other words, existing optical scanners compromise between the scanning area and the reconstruction accuracy. Accordingly, the present study proposes a new scanning system including a zoom-lens unit, which combines both a wide scanning area and a high 3D reconstruction accuracy. In the proposed approach, the object is scanned initially under a suitable low-magnification setting for the object size (setting 1), resulting in a wide scanning area but a poor reconstruction resolution in complicated regions of the object. The complicated regions of the object are then rescanned under a high-magnification setting (setting 2) in order to improve the accuracy of the original reconstruction results. Finally, the models reconstructed after each scanning pass are combined to obtain the final reconstructed 3D shape of the object. The feasibility of the proposed method is demonstrated experimentally using a laboratory-built prototype. It is shown that the scanner has a high reconstruction accuracy over a large scanning area. In other words, the proposed optical scanner has significant potential for 3D engineering applications.

We present a fast Hall effect measurement system that can be used at high temperature. The use of a homogeneous high field permanent magnet in a Halbach configuration allows fast measurements in various DC and AC current fields with step and continuous measurement modes. The results are presented of measurements on platinum film at room temperature and Ge and BiCuSeO between 300 K and 650 K.

Mold monitoring has been more and more widely used in the modern manufacturing industry, especially when based on machine vision, but these systems cannot meet the detection speed and accuracy requirements for mold monitoring because they must operate in environments that exhibit intense vibration during production. To ensure that the system runs accurately and efficiently, we propose a new descriptor that combines the geometric relationship-based global context feature and the local scale-invariant feature transform for the image registration step of the mold monitoring system. The experimental results of four types of molds showed that the detection accuracy of the mold monitoring system is improved in the environment with intense vibration.

This paper presents a novel method of measuring spatial rotation angle with a dual-axis micro-electro-mechanical systems tilt sensor. When the sensor is randomly mounted on the surface of the rotating object, there are three unpredictable and unknown mounting position parameters: α, the sensor's swing angle on the measuring plane; β, the angle between the rotation axis and the horizontal plane; and γ, the angle between the measuring plane and the rotation axis. Thus, the sensor's spatial rotation model is established to describe the relationship between the measuring axis, rotation axis, and horizontal plane, and the corresponding analytical equations are derived. Furthermore, to eliminate the deviation caused by the uncertain direction of the rotation axis, an extra perpendicularly mounted, single-axis tilt sensor is combined with the dual-axis tilt sensor, forming a three-axis tilt sensor. Then, by measuring the sensors' three tilts and solving the model's equations, the object's spatial rotation angle is obtained. Finally, experimental results show that the developed tilt sensor is capable of measuring spatial rotation angle in the range of  ±180° with an accuracy of 0.2° if the angle between the rotation axis and the horizontal plane is less than 75°.

All present watt balances employ permanent magnet systems using a yoke with high permeability as flux return. Very often these systems are built with vertical and azimuthal symmetries. In its simplest form, the air gap is defined as the radial distance between an inner and outer yoke with the same height. This design leads to sloped field lines away from the plane of vertical symmetry. In order to suppress this vertical magnetic field, we propose two modified magnet constructions: (1) adding a permanent magnet in the outer yoke, and (2) decreasing the height of the outer yoke. Finite element method simulations show that, with reasonable optimization, either proposal can lower the vertical magnetic field by about one order of magnitude.

We present a method to improve the accuracy of velocity measurements for fluid flow or particles immersed in it, based on a multi-time-step approach that allows for cancellation of noise in the velocity measurements. Improved velocity statistics, a critical element in turbulent flow measurements, can be computed from the combination of the velocity moments computed using standard particle tracking velocimetry (PTV) or particle image velocimetry (PIV) techniques for data sets that have been collected over different values of time intervals between images. This method produces Eulerian velocity fields and Lagrangian velocity statistics with much lower noise levels compared to standard PIV or PTV measurements, without the need of filtering and/or windowing. Particle displacement between two frames is computed for multiple different time-step values between frames in a canonical experiment of homogeneous isotropic turbulence. The second order velocity structure function of the flow is computed with the new method and compared to results from traditional measurement techniques in the literature. Increased accuracy is also demonstrated by comparing the dissipation rate of turbulent kinetic energy measured from this function against previously validated measurements.

In Hüser et al (2013 Meas. Sci. Technol. 24 115008), we have realized two errors in the calculations of the effect of damping in the vicinity of the surface. The error did not have a quantitatively visible impact on the geometric distortion, but is visible in the phase signal.