Showing papers in "Nondestructive Testing and Evaluation in 2023"
TL;DR: In this paper , a model of Elman neural network optimised by whale optimisation algorithm (WOA) with principal component analysis (PCA) based on singular value decomposition (SVD) was proposed for terahertz (THz)-based thickness measurement of TBCs.
Abstract: Thickness of thermal barrier coatings (TBCs) is closely related to the performance of hot-section components in aero-engine. In this paper, a model of Elman neural network optimised by whale optimisation algorithm (WOA) with principal component analysis (PCA) based on singular value decomposition (SVD) was proposed for terahertz (THz)-based thickness measurement of TBCs. First of all, the theoretical model of THz propagation in TBC is employed to generate simulated signals to meet the demand of sample size for Elman neural network training. Second, PCA based on SVD is used to reduce the dimension of each signal. In order to decrease the possibility of falling into local optimisation and improve the output accuracy of neural network, the weights and biases of network are optimised by WOA. Finally, the performance of the models was evaluated by statistical assessments. Our results show that the thickness measurement method combined with hybrid machine learning adopted in this paper have improved the accuracy of thickness measurement and occupied great potential applications on thickness measurement of TBCs.
3 citations
2 citations
TL;DR: In this article , an efficient numerical scheme and corresponding fast solver are proposed and implemented for rapid and high-accuracy numerical calculation of the motion-induced eddy current testing (MIECT) forward problems.
Abstract: In this paper, an efficient numerical scheme and corresponding fast solver are proposed and implemented for rapid and high-accuracy numerical calculation of the motion-induced eddy current testing (MIECT) forward problems. First, inspired by the time-domain numerical formulation of the MIECT problem, a DFT-based numerical scheme in the frequency-domain was proposed through DFT of the transient excitation magnetic field signals at conductor surface caused by the moving permanent magnet of the MIECT probe. Second, a fast-forward simulator was implemented by further improving the existing Ar code for single-frequency ECT problem and adopting databases approach using the unflawed field information solved and stored a priori. As the key of the fast simulation of the MIECT signal perturbed by defects, a scheme to calculate the pickup signal perturbations was proposed and validated based on the reciprocity theorem. Finally, the validity of the numerical schemes and corresponding fast-forward solver was verified through comparing simulation results with experimental signal. Compared with the full analysis domain methods, the fast simulator can save computational burden up to 1000 times on the premise of not affecting the numerical precision, which enables its being adopted in the inverse analysis of MIECT signals for defect sizing.
1 citations
TL;DR: In this article , a rapid diagnosis algorithm based on the wavelet packet energy and support vector machine method was developed for quick evaluation of the epoxy protective coating, which can be effectively employed for the coating monitoring application.
Abstract: A reliable and effective diagnosis of coating structure is important for further maintenance. For the problem of slow detection and identification using terahertz non-destructive testing technology in the industrial inspection, a rapid diagnosis algorithm based on the wavelet packet energy and support vector machine method was developed for quick evaluation of the epoxy protective coating. The process mainly included time domain signal acquisition of various epoxy protective coating samples detected by a terahertz pulse imaging system, wavelet packet energy parameters extraction as the diagnosis feature vectors, classification model establishment based on the support vector machine algorithm and coating status evaluation using a three-class classifier. The influence on classification accuracy by the various feature vectors inputs with the support vector machine classifier was analysed. Satisfying results were achieved when the relative wavelet packet energy was taken as diagnostic features. A strong defective area could be quickly identified and more detail targeted analysis could be implemented as needed. The time spent was significantly reduced compared to the terahertz imaging of the whole area along with the manual judgement. The analysis indicated that the proposed method would be very useful and can be effectively employed for the coating monitoring application.
1 citations
TL;DR: In this paper , a finite element model for the sensor and sample was generated in COMSOL software so the influence of weld bead geometry and microstructure could be predicted and accounted for.
Abstract: Residual stresses can cause compromise in structural integrity; it is desirable to assess residual stresses using non-destructive testing so that effects on structural properties can be predicted. Electromagnetic (EM) sensors can be used to characterise residual stresses in steels accounting for, microstructure and geometry effects. Residual stress characterisation in welded EN S275 steel plates using EM sensors is reported. Low-frequency, low-magnetic field EM sensors were used to assess residual stresses in the plates. A finite element model for the sensor and sample was generated in COMSOL software so the influence of weld bead geometry and microstructure could be predicted and accounted for. This allowed residual stresses to be determined from EM sensor measurements, excluding the geometry and microstructure effects, XRD was used to verify EM sensor measurements. The highest residual stresses were found adjacent to the weld fusion zone, with magnitudes of, 170±5MPa, 120±20MPa and 42±10MPa for X-ray diffraction (XRD), a small EM sensor (U-12.7) and a big EM sensor (U-31) types, respectively. The differences are due to the volume of the material measured by each measurement type. It was shown that EM sensors are capable of measuring residual stress in welded plates to a good level of accuracy.
1 citations
TL;DR: In this article , a small-volume remote field eddy current sensor with coaxial placement and the differential structure of the detection coil is designed and developed, and the simulation and experimental results show that the magnetic circuit structure and composite shield damping are beneficial to improve the detection capability of the sensor.
Abstract: Multi-layer metal flat structure is an important load-bearing component of the aircraft, with the characteristics of large thickness and complex structure. The structure is prone to produce various defects in the process of its use. The remote field eddy current detection technology is not limited by the skin effect and can penetrate the measured component with large thickness. In view of the large volume of traditional remote field eddy current sensor, which is difficult to apply to complex detection environment, a small-volume remote field eddy current sensor with coaxial placement and the differential structure of the detection coil is designed and developed. The simulation and experimental results show that the magnetic circuit structure and composite shield damping are beneficial to improve the detection capability of the sensor. Setting the balance coil greatly reduces the effect of the direct-coupled magnetic field on the detection coil and improves the sensitivity of the sensor. The detection signal of the remote field eddy current sensor is directly proportional to the defect equivalent volume, and within a certain defect size range, if the defect equivalent volume is similar, the remote field eddy current sensor is more sensitive to the defect depth.
1 citations
TL;DR: In this article , an axial stress measurement method with only a single longitudinal/transverse transducer for tightened bolts based on a novel attenuation-based model is introduced, where ultrasonic responses under axial preload in different frequency bands are comprehensively reflected through the energy attenuation coefficient matrix.
Abstract: Accurate assessment and monitoring of axial stress during the service life of the bolt connection is of great significance in ensuring the stability and reliability of the aerospace structure. The current acoustoelastic method requires both transverse and longitudinal mode waves and is less sensitive to small-size bolts, resulting in relatively larger errors in the evaluation of axial stress. In this paper, an axial stress measurement method with only a single longitudinal/transverse transducer for tightened bolts based on a novel attenuation-based model is introduced. The ultrasonic responses under axial preload in different frequency bands are comprehensively reflected through the energy attenuation coefficient matrix. In addition, an experimental method for selecting the optimal frequency band is given. Furthermore, the semi-permanent coupling method is proposed to provide a stable coupling condition to verify the feasibility of the attenuation-based model. Loading tests and ultrasonic tests were conducted on two kinds of strength-grade materials to obtain the calibration curves of both the longitudinal and transverse attenuation models. The experimental results show that the energy attenuation coefficient is positively correlated with the axial stress in a specific frequency range and the calibrated curve has a high fitting rate with a quadratic fitting function. The average relative error of the prediction results is less than 7.5%, which is better than the conventional acoustoelastic effect model.
1 citations
TL;DR: In this article , a transformer model of an eddy current sensor was proposed to measure the conductivity of thin metal films, and the experimental results were then compensated using the estimated errors.
Abstract: Currently, most commercial measuring instruments for electrical conductivity are primarily used to measure the conductivity of thick specimens. However, measuring the conductivity of thin films with these instruments can be challenging due to the limitation of skin depth. To address this issue, a conductivity measurement method for metal films has been proposed based on the transformer model of an eddy current sensor. It can be found that the phase of impedance change is related to the thickness and conductivity of the specimen when the thickness of the specimen is less than the skin depth. To validate the method, a finite element model is employed to simulate it, and the relative errors of conductivity measurements are analysed. The experimental results are then compensated using the estimated errors, and the influence of excitation frequency is evaluated. Finally, specimens with different conductivities and thicknesses are prepared to verify the method. The results indicate that the relative errors fall within 7.36% before compensation and within 5.25% after compensation, which demonstrates the feasibility of the proposed method for conductivity measurement of metal films.
1 citations
TL;DR: In this article , the amplitude of the multiple sidebands of the modulation spectrum as feature variables and the structural integrity as target variables were used for training and testing the machine learning model.
Abstract: The vibro-acoustic modulation (VAM) method assesses the integrity of a structure using modulation of a high-frequency probe wave and a low-frequency pump wave and measuring the modulation index. A large body of studies found that the modulation index could be used for the defection of contact-type defects in different materials. However, it was also found that the performance of this method is dependent on the probe wave frequency selection. To enhance the robustness of this method, researchers made efforts to modify the VAM method raising the complexity of the equipment and related operator skills, creating needs for extra preparation or procedures. All of these limits VAM potential for industrial application. To develop a robust, efficient, and fast VAM-based non-destructive testing method, the machine learning algorithm was employed. The algorithm utilises amplitude of the multiple sidebands of the modulation spectrum as feature variables and the structural integrity as target variables for training and testing the machine learning model. The experimental result shows that the fatigue crack could be detected with an arbitrary probe wave frequency using the applied machine learning approach.
TL;DR: In this paper , the triaxial compression test and acoustic emission (AE) monitoring test of the CGFB were carried out, and the strength characteristics of defective backfill under seepage-stress coupling were analyzed.
Abstract: Aiming at the problem of seepage-stress coupling failure instability of cemented gangue-fly ash backfill (CGFB) with defects, the triaxial compression test and acoustic emission (AE) monitoring test of the CGFB were carried out in this paper. The strength characteristics of defective CGFB under seepage-stress coupling were analysed，the variation rules of AE parameters (ring count, b-value and entropy value) in the failure process were systematically studied. It is found that the AE parameters (ring count, b-value, and entropy value) of backfill with defects under seepage-stress coupling have a ‘mutation’ phenomenon, which can be used as a precursor feature of failure instability of backfill. Combined the grey-cusp catastrophe theory, a failure prediction model of backfill based on AE parameters (ringing count) was established, and the seepage-stress coupling fracture of backfill with defects was effectively predicted, indicating that the model is feasible to predict the seepage-stress coupled failure of backfill with defects. The research results can provide a theoretical basis for stability monitoring and failure prediction of backfill in deep water-rich mines in China.
TL;DR: In this paper , the authors used tensile specimens and acoustic emissionAE parameters are recorded for various failure loadFLs, such as amplitude, ring down counts, duration, rise time, energy, RA value, DA value, hit rate, count rate and energy rate.
Abstract: Acoustic emission (AE) evaluation is an important Nondestructive Testing technique. The technique is a whole field passive technique that detects defects that are growing during the application of force on the structure. At a certain threshold, AE starts emanating from the structure while the structure is stressed by tensile deformation. 18% Ni Maraging steel 250 grade material is widely used in the aerospace industry and exhibits fracture behaviour. In the current study, tensile specimens are used and acoustic emissionAE parameters are recorded. Four types of specimens Type A, Type B, Type C and Type D specimens are designated as heat -affected zone, parent metal, defect -free weldment and weld with notch defect, respectively. These specimens are tensile deformed in order to obtain acoustic emissionAE parameters at 60% of failure load (FL), 60–75% of FL, 75–90% of FL and 90% to FL. AE parameters – amplitude, ring down counts, duration, rise time, energy, RA value, DA value, hit rate, count rate and energy rate – are tabulated for various failure loadFLs. These parameters have vital importance in critical assessment of the structural integrity of 18% Ni Maraging steel 250 structures.
TL;DR: In this paper , a modal acoustic emission (MAE) technique has been explored through experimental investigation in laboratory for its possible, effective applications in the health monitoring of structures with different geometries, namely, plates and truss.
Abstract: Health monitoring of structures is a fertile field of research. Different techniques are being developed through research to perform the health monitoring on different types of structures. Acoustic emission (AE) technique is considered to be promising, as this technique can be used for damage detection in real time. However, AE technique has some limitations as far as geometry of structure is concerned. Here in this study, modal AE (MAE) technique has been explored through experimental investigation in laboratory for its possible, effective applications in the health monitoring of structures with different geometries, namely, plates and truss. MAE technique is adopted as it facilitates an analysis of structural behaviour under the application of an AE source along with source localisation. Further, a methodology is proposed to minimise the effects of geometry and boundaries/edges. The methodology is based on identifying the front part of the time-frequency representation (TFR) diagram, i.e. first few energetic zones in the TFR, of an AE signal, followed by the alignment of these zones with respect to the contour of the group velocity curves of Lamb modes. The efficacy of the proposed method for damage localisation has been verified and found to be promising.
TL;DR: In this article , a sinogram Transformer method based on a priori projection data is proposed to solve this extremely sparse data complementation problem on a large-scale electron accelerator X-ray in-situ CT system.
Abstract: X-ray CT is an important in-situ non-destructive testing method that plays an important role in both production and materials research. In-situ CT of concrete can acquire images of concrete slices in the state of holding force loading, which is meaningful for the study of concrete crack development characteristics. However, existing X-ray CT equipment either cannot penetrate large reinforced concrete due to energy limitations or does not address the extremely sparse angular reconstruction problem associated with in-situ testing. In this paper, a sinogram Transformer method based on a priori projection data is proposed to solve this extremely sparse data complementation problem on a large-scale electron accelerator X-ray in-situ CT system. The simulated concrete sparse-view projection data and the full projection data are used as the input and label of the proposed method in order to experiment the method. The results demonstrate the feasibility of using a priori projected sine diagrams with ultra-sparse sine diagram residuals to track sine diagram variation, and verify that structures such as cracks and reinforcement, which dominate the deformation residuals of sinograms in concrete sections, can also be successfully recovered using Transformer in the ultra-sparse view projection of views 4–8.
TL;DR: Wang et al. as mentioned in this paper used the most representative feature vectors generated by feature extractor as memory items to represent background information and introduced a metric learning module to make the memory items have the ability to fully represent the background and enhance robustness.
Abstract: Traditional detection algorithms of pipeline non-destructive testing extract information from a large number of defect samples to ensure the detection performance, but even if an adequate of defect samples are collected, it is difficult to enumerate the possible defect morphology in nature. In this paper, we proposed a new semi-supervised anomaly detection algorithm to solve the existing problems. We consider using the most representative feature vectors generated by feature extractor as memory items to represent background information. In addition, this paper also imports a few defect samples to form a semi-supervised structure in the training stage and introduces a metric learning module to make the memory items have the ability to fully represent the background and enhance robustness. To prove the effectiveness of our algorithm, this paper has verified its performance in micro-size pipeline defects. In the experiment, the high-definition industrial camera was used to scan and record the image sequence from the inner surface of the pipeline sample. The latest anomaly detection algorithms have been used as a platform for objective performance evaluation. The result shows our algorithm is more effective in pipeline defect detection and has strong robustness for anti-interference.
TL;DR: In this article , a computationally efficient numerical model for nonlinear dynamic analysis of vertically oriented cracked blades is developed, which can be used for developing a robust vibration-based condition monitoring for a given application which involves hanging beams with a possibility of crack.
Abstract: Dynamics of vertically oriented blades is an important topic of research as it replicates the physical behaviour of several real-time applications such as horizontal axis wind turbine blades. It is observed that available literatures explaining the effects of gravity on the dynamic behaviour of vertical beams/blades did not focus on the various operational adversities such as geometric nonlinearities, possibilities of crack initiation due to adverse conditions. Therefore, in present study, an attempt is made to capture reverberations of gravity on cracked vertical blades including geometric nonlinearity. A computationally efficient numerical model for nonlinear dynamic analysis of vertically oriented cracked blades is developed. Efficacy of proposed model is verified by several case studies. Subsequently, parametric investigation is performed for combined effects of crack and gravity on the dynamic response. Crack and gravity dominant regions based on slenderness ratio are identified for the first time . Furthermore, influence of nonlinearities on such behaviour provides useful insights to anticipate the mechanics of the dynamic behaviour of a vertical cracked cantilever beam. Proposed work may be useful for developing a robust vibration-based condition monitoring for a given application which involves hanging beams with a possibility of crack such as rotor blades.
TL;DR: Wang et al. as discussed by the authors used the Swin-Transformer model to evaluate and classify roughness directly on colour images of milled samples acquired in a convertible image environment, which was taken in a completely dark environment and in an environment disturbed by light sources, such as LED energy-saving lamps during the day.
Abstract: ABSTRACT Current machine vision methods for surface measurement rely excessively on feature design to quantify surface morphology and build predictive models, but metric design suffers from human intervention, and data acquisition is heavily dependent on light source environment and shooting angle. This paper uses the Swin-Transformer model to evaluate and classify roughness directly on colour images of milled samples acquired in a convertible image environment. The images used in the experiment are taken in a completely dark environment and in an environment disturbed by light sources, such as LED energy-saving lamps during the day. By using two kinds of lenses and combining custom light sources and ordinary light sources, respectively, and for different angles, it deeply simulates the environment of online inspection of industrial production. The roughness classification results prove that the method has very good robustness to light source environment and shooting angle, avoiding the artificial design and extraction of image features. The accuracy of the validation set of samples can reach 98.94%, while the accuracy of the test set can reach 97.54%. To wrap it up, the method provides an optimised strategy for visual roughness measurement in industrial production.
TL;DR: In this paper , a nonlinear detection method based on subharmonic modulation is proposed in order to detect the debonding damage of composite stiffened structures in the case of aerospace composite panels.
Abstract: As one of the high-strength structures of the aerospace composite panels, the bonding of the stiffened skins affects the mechanical properties of the overall structure. A nonlinear detection method based on subharmonic modulation is proposed in order to detect the debonding damage of composite stiffened structures in the present paper. The debonding damage interface is simplified to a two-degree-of-freedom nonlinear model using interface contact theory. The multi-scale method is employed to analyse the generation mechanism of subharmonic modulation. The experiment is performed on the composite stiffened plate. Then based on the frequency response function characteristics of in-situ piezoelectric actuator/sensor, both high- and low-frequency excitation signals are applied to the composite stiffened plate, and the debonding damage of stiffeners is identified by the subharmonic modulation component in the response signal spectrum. It is shown, both theoretically and experimentally, that the subharmonic modulation method can effectively detect the interfacial debonding damage of composite stiffened structures and is insusceptible to the interference of environmental noise and the inherent nonlinearity of materials.
TL;DR: In this paper , the influence mechanism of initial defects on the internal crack evolution law and damage destruction of cement superfine tailings backfill (CSTB), uniaxial compression and simultaneous acoustic emission (AE) tests were carried out on CSTB with different degrees of internal initial defects constructed by doping with different contents of doping agent(DA), and the AE b-value, amplitude fractal dimensional time series characteristics and three-dimensional distribution law of CSTBs were analyzed.
Abstract: To clarify the influence mechanism of initial defects on the internal crack evolution law and damage destruction of cement superfine tailings backfill(CSTB), uniaxial compression and simultaneous acoustic emission (AE) tests were carried out on CSTB with different degrees of internal initial defects constructed by doping with different contents of doping agent(DA), and the AE b-value, amplitude fractal dimensional time series characteristics and three-dimensional distribution law of AE events of CSTBs were analyzed in this paper. The research shows that the doping of DA caused the fluctuation and jump of the CSTB b-value to be significantly enhanced, and the b-value showed two jumps in the loading process. The fractal characteristics of CSTB with different DA doping are better, and the fractal dimension D-value and b-value both show a rapid decreasing trend in the preparation process of the specimen for the occurrence of overall unstable failure. The admixture of DA increases the number of initial defects and non-homogeneity within the CSTB, making the generation of 3D localization points of AE events somewhat random. The results of the study can help to better analyze the unstable failure process of the backfill in the mine hollow area and carry out the corresponding support work.
TL;DR: In this article , a two-mode combination approach by compelling multiple frequencies and effective lengths has been developed to replace the bending rigidity from the cable relationship so the tension can be solved explicitly.
Abstract: The development of vibration-based tension determination has increased in recent years. The effective vibration length concept is one of the most robust methods in dealing with various end-rotational support stiffness. Recently, a two-mode combination approach by compelling multiple frequencies and effective lengths has been developed to replace the bending rigidity from the cable relationship so the tension can be solved explicitly. This paper aims to compare the tension prediction using the effective length concept with two existing methods: linear regression and the two-mode combination. Three cases of cable support: hinged-hinged (Case 1), hinged-fixed (Case 2), and fixed-fixed (Case 3), are studied through numerical simulation. The cable is vibrated under random excitation, and its dynamical properties are extracted through the SSI method. Equivalent frequencies and equivalent-effective lengths are computed to perform the two-mode approach. The study shows that linear regression produces more minor errors than the two-mode combination method, either for Cases 1, 2, or 3. The theoretical results are presented to figure out the cause of errors. However, linear regression and the two-mode method both produce promising results in calculating the cable tension in these three cases. Similar results are also shown in the study using experimental laboratory test data.
TL;DR: In this paper , a high-speed eddy current testing system is developed to experimentally investigate the influence of coil gap, detection speed, and the lift-off on the probe's response under moving conditions.
Abstract: Rolling contact fatigue (RCF) cracks online detection using eddy current testing (ECT) is in urgent demand. However, RCF cracks detection and evaluation in this way under moving conditions remains challenging due to the velocity effect in ECT. This paper aims to study the response of a transmitter-receiver eddy current probe to cracks under moving conditions and evaluate the depth and inclination angle of RCF cracks. In this paper, a high-speed eddy current testing system is developed to experimentally investigate the influence of coil gap, detection speed, and the lift-off on the eddy current probe’s response under moving conditions. In addition, the temporal and amplitude features of the eddy current signal are extracted to characterise the depth and inclination angle of the RCF cracks. The experimental results indicate the eddy current probe’s response can be improved by increasing the coil gap (coil centre distance) suitably, which can be done to compensate for the attenuation of the eddy current signal caused by detection speed and lift-off. The probe’s response hardly changes with an increase in detection speed when the driver and pick-up coils of the eddy current probe completely overlap. The crack depth and inclination angle can be evaluated under moving conditions.
TL;DR: In this paper , a series of artificial flat-bottomed holes (FBHs) defects of Honeycomb Sandwich Composites (HSCs) were prepared for pulse thermography and LFM-Chirp-Square pulse-compression thermography (PuCT).
Abstract: Honeycomb Sandwich Composites (HSCs) have been widely used in aerospace and aircraft industries because of their high temperature and corrosion resistance, etc. As defects and damage to HSCs are unavoidable, non-destructive testing (NDT) is essential to ensure the reliability of HSCs. A series of artificial flat-bottomed holes (FBHs) defects of HSCs were prepared for pulse thermography (PT) and LFM-Chirp-Square pulse-compression thermography (PuCT). LFM-Chirp-Square PuCT has the advantage of frequency modulation over PT to detect different depth ranges of FBHs defects. In order to improve the efficiency of defect detection, pulse phase thermography (PPT) and total harmonic distortion (THD) techniques were applied to process the infrared image sequences. The results show that THD processing technique outperforms the PPT processing technique in improving the signal-to-noise ratio (SNR) from feature images. The combination of LFM-Chirp-Square PuCT and THD techniques can be applied to improve the defect detection identification results in HSCs.
TL;DR: In this paper , the authors used ground-penetrating radar (GPR) and ultrasonic echo array (UEA) to track damage progression in the columns of two full-scale reinforced concrete (RC) bridge column-footing subassembly laboratory specimens.
Abstract: Fusion-based imaging using ground-penetrating radar (GPR) and ultrasonic echo array (UEA) was employed to track damage progression in the columns of two full-scale reinforced concrete (RC) bridge column-footing subassembly laboratory specimens. The specimens had different lap-splice detailing and were subjected to reverse-cyclic lateral loading simulating a subduction zone earthquake. GPR and UEA scans were performed on the east and west faces of the columns at select ductility levels. Reconstructed images were obtained using the extended total focusing method (XTFM) and fused using a wavelet-based technique. Composite images of each column's interior were created by merging the images from both sides. A quantitative analysis based on the structural similarity (SSIM) index accurately captured damage progression. A backwall analysis using the amplitude of the backwall reflector was also performed. Changes as early as in the first measurement (μ = 0.5 displacement ductility level) could be detected. Damage variation along the column height was observed, consistent with greater damage at the base. The proposed analyses distinguished the structural behavior differences between the two specimens. In summary, the SSIM metric provides a valuable tool for detecting changes, while the backwall analysis offers simple yet informative insights into damage progression and distribution in full-scale RC members.
TL;DR: In this paper , a nonlinear vibro-acoustic modulation (VAM) based study was carried out, aiming at investigating the influence law between the excitation signal form and the nonlinear effect of sensing signals through both finite element analysis (FEA) and experimental validation.
Abstract: For challenges of early microcrack monitoring of reinforced concrete (RC) structures, a nonlinear vibro-acoustic modulation (VAM) based study was carried out, aiming at investigating the influence law between the excitation signal form and the nonlinear effect of sensing signals through both finite element analysis (FEA) and experimental validation. The mechanism of the nonlinearity in sensing signals coming from microcrack surface vibration collisions due to the breathing effect was found which is the theoretical basis of the VAM-based damage detection. The results show that the nonlinear modulation effect is the highest at the resonant frequency of the structure. The side frequency (SF) amplitude of VAM-based sensing signal in the RC beams with microcracks (damage degree between 0% and 70%) is obvious, but when the cracks continue developing, the effective contact area decreases sharply during the crack opening and closing process due to the nonlinear contact between interfacial crack surfaces. As the width of microcrack is altered from 0 nm to 100 nm, the normalised nonlinear coefficient β is reduced from 0.4 to 0.06 in the approximate form of power function, which can be used to characterise the damage development of the early cracks in RC structures.
TL;DR: In this article , the nonlinear effect caused by the heterogeneous structure of carbon fiber reinforced polymer (CFRP) components was investigated and nonlinear frequency mixing of counter-propagating A0-S0 mode Lamb waves was numerically and experimentally investigated in the CFRP composite plate.
Abstract: Delamination is unavoidable during the fabrication or utilisation of carbon fibre reinforced polymer (CFRP) components. Due to the high sensitivity of the A0 mode for detecting delamination, nonlinear frequency mixing of counter-propagating A0-S0 mode Lamb waves was numerically and experimentally investigated in the CFRP composite plate. Considering the nonlinear effect caused by the heterogeneous structure of CFRP composite, the counter-propagation of primary Lamb waves can minimise the nonlinear interaction induced by material nonlinearity compared to the one-way propagation. Numerically, the nonlinear interaction between primary Lamb waves and delamination was investigated. Moreover, delaminations with different sizes, depths, and interface gaps were explored. It was found that the acoustic nonlinear parameter grows with expanding delamination size and diminishes with increasing delamination depth and interface gap. Furthermore, the nonlinear frequency mixing of counter-propagating A0-S0 mode Lamb wave was experimentally performed. The nonlinear frequency mixing effect induced by the delamination can be maximally isolated from the material nonlinearity. Consequently, the technique based on the nonlinear frequency mixing of counter-propagating A0-S0 mode Lamb waves provides a potential and effective method to detect defects in the composite plate with heterogeneous structures.
TL;DR: In this article , a novel damage detection method based on fractal dimension is proposed, in which the phase-based optical flow is introduced, which is a vision-based measurement method that can calculate the structural vibration with high-spatial-resolution.
Abstract: The most prominent features of fractal dimension analysis are high sensitivity to damage and instant determination of damage location. However, an intrinsic deficiency is that it is difficult to identify damage in a structure while suppressing noise simultaneously. In addition, the vibration measurement with low-spatial-resolution is also the main factor restricting the accurate damage location. In this paper, a novel damage detection method based on fractal dimension is proposed, in order to provide the high-spatial-resolution vibration information, the phase-based optical flow is introduced, which is a vision-based measurement method that can calculate the structural vibration with high-spatial-resolution. Then, to detect damage in a structure while suppressing noise, an advanced signal analysis method is proposed, with this method, the fractal dimension (FRAC) is mapped into Difference of Gaussian (DOG) multi-scale space, producing the FRAC-DOG to reveal damage-induced singularities in mode shapes. Finally, a data fusion technique is applied to the proposed method to provide a reasonable damage detection result that maximises the elimination of uncertainty. The numerical and experimental results demonstrate that the proposed method can detect damage with high-precision in noisy environments by comparing it with the existing damage detection methods.
TL;DR: In this paper , the propagation path and mode conversion process of the transmitted surface waves are considered to quantitatively detect the length and angle of inclined surface cracks based on laser ultrasonic technique.
Abstract: In this paper, transmitted surface waves are used to quantitatively detect the length and angle of inclined surface cracks based on laser ultrasonic technique. The interaction between laser-generated surface waves and inclined surface cracks is analysed, and the propagation path and mode conversion process of the transmitted surface waves are considered. Then, the propagation paths of some peaks and troughs of the transmitted surface waves are obtained. Based on the obtained path and modal conversion information, a quantitative detection method for the length and angle of inclined surface cracks is proposed. The finite element method is used to verify the propagation paths and proposed method, and the results show that the arrival time of the theoretical path is consistent with that of the simulation. The relative measurement errors of the surface crack length and angle are less than 15% and 10%, respectively, which verifies the rationality and correctness of the proposed method.
TL;DR: In this paper , a sensitivity-based eigenstrain reconstruction approach is developed for residual stress identification in thin plates using vibrational modal data, where residual stresses are parameterised through direct eigen-strain analysis and residual stress reconstruction is recast as a parameter identification problem whose goal function is just the least-squares of the misfit between the measured and calculated data.
Abstract: Non-destructive evaluation of the spatially resolved residual stresses from limited measurement data is crucial for a comprehensive assessment of structural integrity and performance reliability of engineering components. Generally, residual stresses are caused by incompatible internal eigenstrains and along this line, a novel sensitivity-based eigenstrain reconstruction approach is developed in this work for residual stress identification in thin plates using vibrational modal data. There are two key ingredients in establishing the proposed approach. At first, residual stresses are parameterised through direct eigenstrain analysis and thereafter, residual stress reconstruction is recast as a parameter identification problem whose goal function is just the least-squares of the misfit between the measured and calculated data. Second, to minimise the nonlinear least-squares goal function, the modal sensitivity analysis is called to linearise the misfit and the trust-region constraint is invoked in conjunction with the Tikhonov regularisation to enhance the convergence. Numerical examples are investigated to verify the robustness, accuracy and efficiency of the proposed approach.