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Functionally gradient material (FGM) in service often experience temperature variations that can affect the propagation characteristics of guided waves. This investigation aims to study the propagation of thermoelastic guided waves in the FGM plate. A computational method for the state vector and Legendre polynomials hybrid approach, which is proposed based on the Green–Nagdhi theory of thermoelasticity. The heat conduction equation is introduced into the governing equations, and optimized using univariate nonlinear regression for arbitrary gradient distributions of the material components. To study their dispersion characteristics, a non-hierarchical calculation for the dispersion curves of FGM plates versus temperature is realized. In addition, a frequency domain simulation model is developed and compared with theoretical data to evaluate the accuracy and feasibility of the proposed theory. Then, the influence of Legendre orthogonal polynomial cut-off order on dispersion curve convergence is investigated. Subsequently, the shift of the gradient index and temperature variation on the fundamental mode in dispersion curve is analyzed. The results indicate that changes in both gradient index and temperature lead to a systematic shift in the phase velocity of fundamental modes in the low frequency range. Meanwhile, anti-symmetric modes exhibit higher sensitivity. On this basis, the study can provide theoretical support for the acoustic non-destructive characterization of FGM plates versus temperature. [ABSTRACT FROM AUTHOR]

This study investigates the correlation between various micromagnetic signature patterns and the yield and tensile strengths of carbon steel (Cr12MoV steel as per Chinese standards). For this purpose, back-propagation neural network (BP-NN) models are established to quantitatively predict the yield and tensile strengths of carbon steels. The accuracy of prediction models is significantly affected by the presence of redundant micromagnetic signature patterns. By carefully screening the input parameters, it is able to effectively mitigate prediction errors arising from unreasonable model inputs. In the field of micromagnetic nondestructive testing (NDT), prediction models calibrated for a specific instrument or sensor cannot be directly applied to another instrument or sensor. In the study, a joint distribution adaptation transfer learning strategy based on auxiliary data is proposed to enhance the generalization of prediction models for cross-instrument applications. When auxiliary data accounts for 30% of the source domain data, the joint distribution adaptation transfer learning method based on auxiliary data improves the robustness of the model. The accuracy of the yield strength and tensile strength calibration models witnesses remarkable improvements of approximately 91.4% and 93.5%, respectively. [ABSTRACT FROM AUTHOR]

Magnetostriction-based electromagnetic acoustic transducer (M-EMAT) is a promising tool for generating fundamental shear-horizontal (SH0) mode guided waves in plate. Though the M-EMAT possesses high-order harmonics excitation ability in nature, its conventional way can only generate a fundamental component of SH0 mode. The analytical modeling was performed in this study to releasing the ability of M-EMAT in generating odd harmonics of SH0 mode. First, the inaccurate conditions of magnetic fields for relative permeability calculation in the existing model are corrected in the proposed model. Second, the error of the existing model in predicting the spectrum of the SH0 mode generated in Nickel plate is estimated. Third, numerical solutions are provided by the improved model to examine the key factors governing the ability of M-EMAT in generating odd harmonics of SH0 mode. The conclusions demonstrated that the intensity ratio (HS/HD) of static and dynamic magnetic fields is adjusted below 1 and the ability of M-EMAT in generating odd harmonics of SH0 mode can be activated. The normalized amplitude of 3rd harmonics decays exponentially with the increase of HS/HD, which is independent of geometrical parameters of M-EMAT. The improved model can effectively optimize excitation parameters of M-EMAT and generate odd harmonics of SH0 mode in plate. [ABSTRACT FROM AUTHOR]

The service life and structural safety of components are affected by the thermal ageing of materials; therefore, a non-destructive evaluation of materials is extremely essential and crucial. In this work, heat-resistant steel Cr12MoV was selected as a specimen, and the embrittlement period of heat-resistant steel Cr12MoV was obtained by accelerated thermal ageing experiments. The effects of service temperature and service time on the mechanical properties of heat-resistant steel were analysed. The non-destructive testing of heat-resistant steel was carried out by using magneto-acoustic compound detection techniques based on electromagnetic acoustic transducers. In the process, magneto-acoustic compound detection signals were decoupled. The electromagnetic characteristic parameters and ultrasonic characteristic parameters of the detection signals were extracted to evaluate the mechanical properties and thermal ageing of heat-resistant steel. The quantitative evaluation ability of thermal ageing brittleness of heat-resistant steel was improved by using the magneto-acoustic compound detection techniques compared with single eddy current detection method or single ultrasonic detection method. [ABSTRACT FROM AUTHOR]

The correlation between magnetic Barkhausen noise (MBN) features and the surface hardness of two types of die steels (Cr12MoV steel and S136 steel in Chinese standards) was investigated in this study. Back-propagation neural network (BP-NN) models were established with MBN magnetic features extracted by different methods as the input nodes to realize the quantitative prediction of surface hardness. The accuracy of the BP-NN model largely depended on the quality of the input features. In the extraction process of magnetic features, simplifying parameter settings and reducing manual intervention could significantly improve the stability of magnetic features. In this study, we proposed a method similar to the magnetic Barkhausen noise hysteresis loop (MBNHL) and extracted features. Compared with traditional MBN feature extraction methods, this method simplifies the steps of parameter setting in the feature extraction process and improves the stability of the features. Finally, a BP-NN model of surface hardness was established and compared with the traditional MBN feature extraction methods. The proposed MBNHL method achieved the advantages of simple parameter setting, less manual intervention, and stability of the extracted parameters at the cost of small accuracy reduction. [ABSTRACT FROM AUTHOR]

This research delves into the characterization of the ultrasonic transmission coefficient pertaining to various types of bonding defects in Fiber-Reinforced Polymer (FRP)-bonded structures. Initially, an ultrasonic transmission coefficient calculation model for FRP-bonded structures in a water immersion environment is established. This model is used to analyze the variation in the ultrasonic transmission coefficient under different defect types, namely intact bonding, interfacial slip, and debonding defects. Subsequently, a frequency domain finite element analysis model of FRP-bonded structures with different defect types is constructed. The simulation validates the accuracy of the theoretical analysis results and concurrently analyzes the variation in the transmission signal when the defects alter. Lastly, an experimental platform for water immersion ultrasonic transmission measurement is set up. The transmission signals under different defect types are extracted through experiments and evaluated in conjunction with theoretical calculations to assess the types of bonding defects. [ABSTRACT FROM AUTHOR]

The experimental study of ultrasonic transmission coefficient measurement method was carried out for the problem of bonding quality inspection of bonded structures of composites with thick adhesive layer. For the uniaxial CFRP bonded specimens, the ultrasonic waves' phase velocity distribution and the ultrasonic transmission coefficient spectrums were measured by the water-immersion ultrasonic transmission method. Then their complex elastic constants were inversed by the particle swarm optimization algorithm based on simulated annealing. Based on this, CFRP bonded specimens in perfect bonding status and having single weak bonding interface, dual weak bonding interfaces were manufactured. Then the ultrasonic transmission coefficient spectrums were measured, and the distinction of bonding quality between different bonding specimens was predicted. At the same time, according to the shift characteristics of the measured ultrasonic transmission coefficient spectra, the influence of the symmetry of the CFRP bonded structures with thick adhesive layers on the ultrasonic transmission coefficient spectrums was investigated experimentally. In addition, by comparing the time-domain and coefficient spectra characteristics of transmitted waves, the advantage of using the coefficient spectrum measurement method in bonding quality detection was expounded. [ABSTRACT FROM AUTHOR]

In this research, to solve the problem of the ultrasonic guided wave inspection of a U-shaped boom, an improved periodic permanent magnet electromagnetic acoustic transducer (PPM EMAT) is proposed for defect detection for a U-shaped boom. The acoustic field distribution range of a traditional PPM EMAT is approximately ±20°, and the energy distribution is relatively concentrated. By adjusting the tilt angle between adjacent magnets and coils of a traditional PPM EMAT, an improved PPM EMAT is proposed. The acoustic field distribution range of the improved PPM EMAT is approximately ±30°, and the energy distribution in this range is relatively uniform. The simulation and experimental results show that the improved PPM EMAT has superior frequency response characteristics and acoustic field directivity, which is suitable for detecting large and complex structures. Furthermore, based on the traditional PPM EMAT and the improved PPM EMAT array, combined with the reconstruction algorithm for the probabilistic inspection of damage (RAPID), the damage locations of the double-hole defects of a U-shaped boom are studied. It is shown that the imaging results for defect location using the improved PPM EMATs are better than those found using the traditional PPM EMATs. [ABSTRACT FROM AUTHOR]

Truck cranes are indispensable heavy-duty loading and unloading equipment in industrial production. A boom is the key load-bearing component of a truck crane, and its health has a vital influence on a crane's lifting performance and safety in production. Therefore, it is urgent to develop a structural health monitoring (SHM) method for a boom structure. In this research, an improved intelligent defect location algorithm based on helical guided waves is applied to the defect detection of a U-shaped boom. The improved intelligent algorithm is a defect location algorithm based on the ellipse imaging principle, which combines an evolutionary algorithm with a K-means algorithm and can identify the location of defects through the distribution of individuals. According to the propagation characteristics of the helical guided waves in the structure of a U-shaped boom, an optimization scheme for the improved intelligent defect location algorithm is proposed that fully considers the fact that the group velocity of the helical guided waves varies with the wall thickness, and the corresponding group velocity is used to accurately calculate the arrival time of each initial individual to improve the accuracy of the defect location. Numerical simulations and experiments are conducted to verify the effectiveness of the proposed improved intelligent defect location algorithm in the defect location algorithm. When only one group velocity is considered, the improved intelligent defect location algorithm is in good agreement with the elliptical imaging algorithm. When the group velocities for different wall thicknesses are fully considered, the detection results of the optimized intelligent defect location algorithm have a higher resolution. This optimization algorithm provides a tool for the SHM of a U-shaped boom based on guided waves. [ABSTRACT FROM AUTHOR]

Fe-based amorphous coatings prepared by high-velocity oxy-fuel (HVOF) spraying have the advantages of good mechanical properties, high density, low porosity, and high amorphous content. The service life and bonding strength of coating greatly depend on its thickness; however, the characterization of ferromagnetic coating thickness is a very difficult problem. Pulsed eddy current (PEC) is characterized by abundant signals in frequency domains. In this paper, the thickness measurement principle of ferromagnetic coating was explored, and the typical and entropy features from PEC signals were extracted. Seven integrated learning methods were combined to quantitatively characterize the coating thickness, namely ridge regression (RR), lasso regression (LR), random forest regression (RFR), extra trees regression (ETR), gradient boosting tree regression (GBTR), addaptive boost regression (ABR) and eXtreme Gradient Boosting Regression (XGBR) algorithms. By comparing typical features with new ones, it was verified that the effective combination of entropy features and typical features could be used as effective feature parameters of eddy current signal. Statistical scores (RMSE and R2) and GridsearchCV features were used to evaluate and optimize the established model. As indicated by the results, the proposed XGBR machine learning model well predicted the coating thickness, and the relative error less than 0.05 mm. [ABSTRACT FROM AUTHOR]

The combination of multifunctional micromagnetic testing and neural network-based prediction models is a promising way of nondestructive and quantitative measurement of steel surface hardness. Current studies mainly focused on improving the prediction accuracy of intelligent models, but the unavoidable and random uncertainties related to instruments were seldom explored. The robustness of the prediction model considering the repeatability of instruments was seldom discussed. In this work, a self-developed multifunctional micromagnetic instrument was employed to perform the repeatability test with Cr12MoV steel. The repeatability of the instrument in measuring multiple magnetic features under both static and dynamic conditions was evaluated. The magnetic features for establishing the prediction model were selected based on the consideration of both the repeatability of the instrument and the ability of magnetic features in surface hardness evaluation. To improve the robustness of the model in surface hardness prediction, a modelling strategy considering the repeatability of the instrument was proposed. Through removing partial magnetic features with higher mean impact values from input nodes, robust evaluation of surface hardness in Cr12MoV steel was realized with the multifunctional micromagnetic instrument. [ABSTRACT FROM AUTHOR]

Harmonic nonlinear ultrasound can offer high sensitivity for residual stress measurements; however, it cannot be used for local stress measurements at a point in space and exhibits nonlinear distortions in the experimental system. This paper presents a feasibility study on the measurement of residual stress in a metal plate using a nonlinear Lamb wave-mixing technique. The resonant conditions for two Lamb waves to generate a mixing frequency wave are obtained via theoretical analysis. Finite element simulations are performed to investigate the nonlinear interactions between the two Lamb waves. Results show that two incident A0 waves interact in regions of material nonlinearity and generate a rightward S0 wave at the sum frequency. Residual stress measurement experiments are conducted on steel plate specimens using the collinear Lamb wave-mixing technique. By setting different delays for two transmitters, the generated sum-frequency component at different spatial locations is measured. Experimental results show that the spatial distribution of the amplitude of the sum-frequency component agrees well with the spatial distribution of the residual stress measured using X-rays. The proposed collinear Lamb wave-mixing method is effective for measuring the distribution of residual stress in metal plates. [ABSTRACT FROM AUTHOR]

Magnetic Barkhausen noise (MBN), sensitive to the microstructure of materials, can be applied in the surface decarburization depth detection of ferromagnetic specimens. However, the effects of core microstructures on the determination results of decarburization depth have not been explored. In this study, MBN was employed to evaluate the magnetic properties of the decarburized 60Si2Mn spring steels with martensitic and pearlitic core microstructures. Spring steel samples were austenitized at different times to generate different decarburization depths. Seven magnetic features were extracted from the MBN butterfly profiles. We used the variation coefficient, linear correlation coefficient, and normalized sensitivity to discuss the influence of the core microstructures on these seven features. The different core microstructures led to a large difference in the ability of MBN features to characterize the decarburization layer depth. However, three features of MBN butterfly profiles demonstrated an approximately linear dependency (linear correlation coefficient > 94%) on surface decarburization depth and monotonically increased with the increase in depth in both core microstructures of spring steels. [ABSTRACT FROM AUTHOR]

In this study, a cylindrical test specimen with a 3D through-hole defect was processed, and the reflected echo data of the defect at different cross-sections were obtained by an ultrasonic testing detection system. On this basis, two data processing methods were designed to obtain two types of 3D reconstruction images of defects, and the reconstruction effects of two methods were compared using the real defects. In general, this study achieved a relatively accurate 3D reconstruction of through-hole defects at a low cost. Our methods provided lower cost than current state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

The correlation between multiple patterns of micromagnetic signatures and the surface hardness of three types of carbon steels (referred as Cr12MoV steel, 45 steel, and martensitic stainless steel of 3Cr13 in Chinese standards) was investigated in this study. Back-propagation neural network (BP-NN) models were established for the quantitative prediction of surface hardness in carbon steels. The quality of the specimens used for calibration (or more precisely the data distribution of the target properties) greatly affected the accuracy of prediction models. The uniformly distributed data were more suitable for establishing high-accuracy BP-NN models. For the data which did not follow a uniform distribution, a two-step modelling strategy of classification and subsequent regression was proposed to improve the accuracy of micromagnetic and quantitative prediction of surface hardness. The proposed two-step modelling strategy integrating the K-nearest neighbor classification (KNN) algorithm with BP-NN modelling method was verified by external validation experiments. [ABSTRACT FROM AUTHOR]

Three mitigation mechanisms can be considered in the design of an impact buffering structure made of granular materials. First, reflection and decomposition of stress wave may occur at the interface of two granules of different materials. Second, energy dissipation happens at the viscoelastic contact region of two adjacent granules. Third, the impact energy carried by stress waves has multiple propagation paths in two- or three-dimensional granular materials. In this study, a two-dimensional square composite structure of spherical granules (SCSPG) employing all the three mitigation mechanisms is designed and optimized as an impact buffering structure. A numerical model is established to investigate the propagation behavior of impact-induced stress wave in a SCSPG composed of viscoelastic spheres. Comprehensive evaluation functions are established to evaluate the impact mitigation performance of the SCSPG based on the consideration that the probability of impact varies with impact location. To reduce the computational complexity in the material optimization process, a two-step strategy integrating a neural network with a genetic algorithm is proposed. The hyperparameters of the neural network are optimized for the purpose of achieving high accuracy with the meta-data generated by solving the numerical model. A selection criterion of an optimal material combination is established with the distribution histogram of fitness function's values. After the optimization, the numerical solutions of stress waves in SCSPG are improved, thus verifying the optimization results obtained by the two-step strategy. After the optimization, the reduction ratios of the values of the contact force-dependent and the velocity-dependent functions exceeded 55% and 53%, respectively. The proposed evaluation functions and the developed optimization algorithm are applicable to the design of high-performance impact mitigation SCSPG. [ABSTRACT FROM AUTHOR]

Functionally graded materials (FGM) have received extensive attention in recent years due to their excellent mechanical properties. In this research, the theoretical process of calculating the propagation characteristics of Lamb waves in FGM sandwich plates is deduced by combining the FGM volume fraction curve and Legendre polynomial series expansion method. In this proposed method, the FGM plate does not have to be sliced into multiple layers. Numerical results are given in detail, and the Lamb wave dispersion curves are extracted. For comparison, the Lamb wave dispersion curve of the sliced layer model for the FGM sandwich plate is obtained by the global matrix method. Meanwhile, the FGM sandwich plate was subjected to finite element simulation, also based on the layered-plate model. The acoustic characteristics detection experiment was performed by simulation through a defocusing measurement. Thus, the Lamb wave dispersion curves were obtained by V(f, z) analysis. Finally, the influence of the change in the gradient function on the Lamb wave dispersion curves will be discussed. [ABSTRACT FROM AUTHOR]

In this paper, a cylindrical aluminum sample with an eccentric circular hole was prepared, and ultrasonic measurements were carried out by experimental means. The measurement area was limited to a plane edge perpendicular to the axis of the cylindrical component. The measured waveform data were input into the formula of approximate correction method, and the section image was obtained by using a modified Born approximation (MBA) method. Then, the three-dimensional (3D) shape of the defects in the aluminum sample was reconstructed by superimposing the cross-sectional images. Results showed that the defect reconstruction effect of the two-dimensional section and the 3D defect reconstruction effect were significantly improved by the MBA method. [ABSTRACT FROM AUTHOR]

Compared with the conventional eddy current, pulsed eddy current (PEC) technology has the characteristic of abundant components in the frequency domain, which is a significant technological advancement. Improvements in the production and performance of PEC sensors are necessary for nondestructive testing. Sensor configuration parameters have significant influence on the development of PEC system. In this study, through finite element simulation and experimental investigation, different optimization methods for PEC sensors are compared and studied. According to the eddy current detection principle, a two-dimensional finite element simulation model was established to study the influence of the shape and size parameters of cone-shaped PEC sensors. Then a cone-shaped PEC sensor was optimized by the orthogonal methodology and the response surface methodology, respectively. To compare the effectiveness of the optimization methods, two optimized sensors were fabricated. It was demonstrated that the combination of finite element method and response surface methodology was superior for improving the detection performance of the PEC sensor compared with the orthogonal methodology. The result also indicated that the developed cone-shaped PEC sensor had a stronger defect detection capability than cylindrical-shaped PEC sensors. The proposed optimization design method provides a feasible reference method for the design of PEC sensors and corresponding parameters. [ABSTRACT FROM AUTHOR]

Since magnetic Barkhausen noise is very sensitive to the change of the stress or residual stress level in components, it is feasible to detect the stress or residual stress profile along the depth direction by the magnetic Barkhausen noise method. An engineering approach was used to validate a theoretical model describing the relationship between magnetic Barkhausen noise and stress magnitude. To generate stress gradients in the specimen of Q235 steel under different deflections, the four-point bending device was used. Then the detected signals obtained in the experiment were divided into different sub-bands to evaluate the stress at different depths. The testing depth was set to be around 100 μm due to the rapid exponential attenuation of the noise signals. In the experiments, the sub-band energy density showed sensitive as the loading displacement increasing. The experimental results showed that the signal energy was also sensitive to the plastic deformation of the material. Within the depth of 100 μm, the stress change was very small. The final experimental results showed that even under such small stress variations, it is sensitive and feasible to use the magnetic Barkhausen noise energy to characterise the change of stress gradients. [ABSTRACT FROM AUTHOR]

In this study, an advanced magnetoacoustic compound inspection method for a high-order Lamb waves mode electromagnetic acoustic transducer (EMAT) was proposed. The proposed EMAT can achieve the excitation and reception of the A1 mode which is the first-order Lamb waves mode. According to the characteristics of the A1 mode EMAT testing signal, a signal processing method for obtaining the pulsed eddy current signal by curve fitting was developed to extract the information for the pulsed eddy current. The voltage of the ultrasonic waves was carried on the pulsed eddy current voltage, and it was obtained by removing the pulsed eddy current voltage and extracting the time-domain testing signal of the A1 mode EMAT. Through A1 mode EMAT single detection that was used to obtain the pulsed eddy current and A1 mode, the multi-parameter from the magnetoacoustic compound testing signal of the A1 mode EMAT could be used to characterize the aluminum plate performance degradation. The detection accuracy of aluminum plate performance degradation was improved by the magnetoacoustic compound inspection compared with a single detection method. [ABSTRACT FROM AUTHOR]

In the study, the three-dimensional (3D) morphology of defects in thin steel strips with a thickness of 0.8 mm was determined with the imaging method of magnetic field distortion (MFD). First, MFD imaging of through-wall defects and wall-thinning defects in the samples collected from inline products was performed in our laboratory. The actual profiles of the defects were measured with a digital microscope. Second, MFD imaging results were compared with the actual shapes of the defects in order to develop a proper 3D reconstruction method of complex defects. Finally, the analysis results demonstrated that the high reconstruction accuracy of opening contours of complex defects could be realized with the carefully selected threshold value of MFD-induced voltage amplitude. The good linear dependency of MFD-induced voltage amplitude on the depth of complex wall-thinning defects was confirmed. Therefore, MFD imaging method is a promising method for accurately reconstructing 3D shape of complex wall-thinning defects in thin steel strips. [ABSTRACT FROM AUTHOR]

Residual plastic deformation induced in low-carbon steels usually demonstrates anisotropy. Eddy current method is applicable for the residual plastic deformation evaluation. However, it is difficult to efficiently evaluate both the principal strain direction and magnitude of residual plastic deformation with the conventional eddy current method. To solve these limitations, a novel method of oscillatory rotating eddy current (OREC) was developed and successfully applied in characterizing the anisotropy of residual plastic deformation in low-carbon steels. The parameters of eddy current response obtained under different frequencies were extracted to characterize the plastic deformation and then the characterization performances of extracted parameters were compared. The compound voltage signal and real part of the impedance could better characterize the residual plastic deformation than the imaginary part of the impedance. It was found that the angle of the major axis of the selected 8-shaped patterns measured with OREC was a good indicator of the principal strain direction. As the residual plastic deformation was increased, the length of the major axis of the 8-shaped patterns monotonously increased despite its sensitivity to the plastic deformation was frequency-dependent. [ABSTRACT FROM AUTHOR]

Imaging algorithms for visualization of defects play a significant role in Lamb wave–based research of nondestructive testing and structural health monitoring. In classical algorithms, the position or distribution of defects is located by mapping the amplitude or phase information of signals from the time domain to every discrete spatial grid of the structure. It is time-consuming. In this study, the diversity, statistical, and fuzzy characteristics of the elliptic imaging algorithm are analyzed first; then, an intelligent defect location algorithm is proposed based on the evolutionary strategy and the K-means algorithm. The position of defects can be identified by observing the distribution of individuals. There are six parts in the proposed algorithm, including the data structure design, adaptive population screening, adaptive population reproduction, diversity maintenance mechanism, and cutoff criterion. Considering the statistical and fuzzy characteristics in the detection, several specific input parameters are defined in our algorithm, such as the distance-dependent screening threshold, path-dependent residual vector, and path-independent residual. To maintain the diversity of individuals in the analysis, we have made two adjustments to the evolutionary strategy: one is to optimize the population screening and reproduction steps with the K-means algorithm, and the other is to add a diversity maintenance method into the evolutionary strategy. The effectiveness of the proposed intelligent defect location algorithm is verified by numerical simulations and experiments. Numerical studies indicate that the proposed algorithm has a reliable performance in the detection of defects with different shapes and sizes. In the experimental research, we demonstrate that the efficiency of the proposed algorithm is about 200 times faster than the elliptic imaging algorithm. And the optimum parameter setting of the algorithm is investigated by analyzing the influence of parameter setting on the detection. [ABSTRACT FROM AUTHOR]

The two-step strategy for 3D reconstruction of complex defects was updated by combining the magnetic field disturbance (MFD) with magnetic flux leakage (MFL) measurement methods. Firstly, the plane-scanned MFD imaging was employed to achieve high-accuracy reconstruction of the opening outlines of complex defects. Secondly, the finite element simulation model of the defect with the recognized opening outline was established as the forward model for depth profile inversion with the particle swarm optimization algorithm. The performances of the conventional MFL-based and updated strategies were carefully compared through finite element simulation. The results proved that the updated method combining MFD signals with MFL signals had the better performance in accurate 3D reconstruction of complex defects than the conventional MFL-based inversion strategy, displaying smaller errors in opening outline, peak depth and the profile. Experimental results confirmed that the updated strategy could accurately reconstruct the 3D shape of 8-shaped defect and rectangular defect with rounded corners. [ABSTRACT FROM AUTHOR]

For an operating wind turbine, the main shaft suffers severe structural damage. The surface breaking transverse crack threatens the safety of drive-train system directly. The crack examination method is available by diffracted waves in the central hole. In this research, an electromagnetic acoustic transducer (EMAT) for receiving diffracted longitudinal waves is proposed. Firstly, the converse piezomagnetic stress coefficients and magnetostriction coefficient were derived from the measured magnetic characteristic curve. The measured parameters were provided for sensor simulation. Considering the two coupling mechanisms, a receiving EMAT model was established for coil optimization. Secondly, the influence of materials, lift-off distance and cable type on sensor impedance would be analyzed in detail. Multiple factors were taken into account for impedance matching, and the signal amplitude was improved significantly. The angle divergence of the EMAT was also measured, showing the main lobe with 24°. The crack detection experiments were carried out on a shaft sample. The results show that the developed EMAT can achieve the reception of diffracted longitudinal waves, and the signals are distinguishable. The crack was evaluated simultaneously by the received diffracted waves, and the errors showed less than 3 mm. [ABSTRACT FROM AUTHOR]

Intelligent defect location algorithms based on the times-of-flight (ToFs) of Lamb waves are attractive for nondestructive testing (NDT) and structural health monitoring (SHM) of structures with large geometric sizes. Unlike the classical imaging algorithm based on projecting the amplitude information of scattering signals into a discrete spatial grid on the structure via their propagation characteristics, intelligent defect location algorithms are more efficient in specific applications. In our previous work, an intelligent algorithm for the location of defects in plates was proposed by considering the statistical, diversity, and fuzzy characteristics of the classical defect location algorithm. This approach can realize the efficient location of different defects under a suitable parameter selection. However, interfering components remain in the results, which decreases the detection resolution. Because the measurement uncertainty is directly related to the time, an optimized intelligent location algorithm is provided for the efficient defect location with Lamb waves and a sparse transducer array in this study. The defect position is identified with high resolution by analyzing the distribution of individuals. Several specific data and a fuzzy control parameter are introduced to the proposed algorithm. The K-means algorithm was adopted to realize the adaptive updating of individuals. The influence of parameter values on the detection results was analyzed. A combined analysis of the individuals was provided to ensure the detection robustness by eliminating the influence of fuzzy control parameters on the detection. Compared with the elliptic imaging algorithm, the intelligent defect location algorithm has higher location resolution and executes approximately 65 times faster. [ABSTRACT FROM AUTHOR]

Since the permeability of ferromagnetic materials is sensitive to the stress changes, it is feasible to acquire the stress level through detecting the change in permeability. In this study, to explore the distribution of stress or residual stress along the depth direction, a multi-layer model was established and a new inversion algorithm was proposed; and the hypothesis of uniformity of the material’s physical properties for each layer was introduced. Under laboratory conditions, the four-point bending experiment was then implemented with a sample of 45# steel. Global Fourier series fitting based on the least-squares method was used for signal process. The amplitude ratio of the induced voltage to the excitation current was extracted. The effective permeability and the associated hysteresis angle at the 0.25 mm deflection were calculated and presented good regular variations. Finally, under the 0.25 mm deflection, the effective permeability change along the depth was obtained, and the inversely fitted curve was consistent with the theoretical curve. It is verified that the sensor has good robustness by adding deviation of the detection depth. Thereby, it is feasible to test stress or residual stress as a function of depth by multi-frequency eddy current (EC) method. [ABSTRACT FROM AUTHOR]

This work presents a new omnidirectional electromagnetic acoustic transducer (EMAT) employing a circumferential periodic permanent magnet array, which was proposed for generating and receiving shear-horizontal (SH) guided waves in an aluminum plate. The novel transducer consisted of 12 axially polarized sector magnets arranged in a circle, and the magnetic field directions of adjacent magnets were opposite. A spiral coil was arranged under the magnet array. A vertical magnetic field generated by the magnets and the circumferential eddy current generated by the spiral coil formed a Lorentz force in a plate acting in the radial direction of this new omnidirectional EMAT. By controlling the sizes of the sector magnets, the omnidirectional SH0 mode (fundamental SH guided wave mode) was generated. To maximize the output of the EMAT at the given excitation frequency, it was proposed to add acrylic spacers between the sector magnets and determine the size of the magnet based on the frequency bandwidth of the excitation signal while also optimizing the omnidirectional sound field. A three-dimensional (3D) finite element model of the EMAT was established using COMSOL Multiphysics to perform numerical simulations, and the effectiveness of the optimization method was verified. The effectiveness was verified by experiments. The simulations and experiments showed that the proposed EMAT could generate omnidirectional SH0 mode guided waves in an aluminum plate. [ABSTRACT FROM AUTHOR]

A large plate like structures can undergo some severe ruptures because of the stress created by the mass and shape. Ruptures are regularly started by surface cracks. For this aim, it is important to evaluate brutality of the noticeable cracks, by constant nondestructive assessments. In this work, a novel method for surface crack depth estimation based on Rayleigh waves by electromagnetic acoustic transducers (EMATs) is introduced. The method is based on a position-time (P-T) graph for direct transmitted Rayleigh waves between fixed transmitter and uniformly movable receiver on surface of the specimen. The process is repeated on different center frequencies both in the experiment as well as in two-dimensional finite element method simulation on steel plates. One of the specimens was without crack while the other one holds surface cracks with the depth ranging from 3–6 mm. Results obtained from simulation and experiment were significant to estimate crack depth with a maximum error of 7.5%. [ABSTRACT FROM AUTHOR]

The Dynamic Magnetostriction (DM) measurement method as a nondestructive testing method of ferromagnetic materials, measures the DM curve using electromagnetic acoustic transducer (EMAT) to characterize material and predict the mechanical properties. Lorentz forces and magnetostriction forces contribute mainly to the ultrasonic generation. Only the range of low field, in which the magnetostriction force mechanism is predominant can be used to measure the DM curve, but the boundaries of this range are uncertain. The improved DM measurement method based on shear wave Magnetostriction EMAT (M-EMAT) is proposed and the theory of generation of shear waves is derived. For the M-EMAT, only magnetostriction force mechanism contributed to the generation of shear waves. A theoretical model for the optimization of the transducer is developed, the model is in good agreement with the experimental results. The microstructure changes caused by residual strain will affect the magnetostriction coefficient and the DM curve. Therefore, the DM curves of low carbon steel specimens with different levels of residual strains are measured by the optimized transducer to characterize the residual strain. The normalized results demonstrate that the slope of the DM curve obviously changes with the residual strain. This leads to the conclusion that the DM measurement method can be used to characterize the residual strain of the low carbon steels. [ABSTRACT FROM AUTHOR]

In traditional methods, features extracted from the hysteresis loop are manually analyzed to establish a model for predicting tensile force in one ferromagnetic material. However, the hysteresis loop is sensitive to material type, thus increasing the difficulty in predicting tensile forces in two materials. Moreover, manual feature extraction is time consuming. It is necessary to complete automatic feature extraction and elimination of the influence of material type on the hysteresis loop in order to automatically establish a prediction model for tensile force prediction in two materials. In this article, an evolutionary computation-based method was proposed to perform the above-mentioned two tasks simultaneously. The proposed method involves three steps. First, hysteresis loops of two materials under different tensile forces were measured. Second, the measured hysteresis loops were transformed into corresponding transformed ascending hysteresis curves through a transformation operation of the curve of hysteresis loop change (CHLC) for eliminating the influence of material type on the hysteresis loop. Third, an improved bat algorithm was proposed to eliminate further the influence of material type on the transformed ascending hysteresis curve. The improved bat algorithm iteratively gave the position of a material type-insensitive feature on the transformed ascending hysteresis curve. The material type-insensitive feature-based neural network was used to predict tensile forces in two materials. Experimental results verified the proposed method. The motivation of obtaining a general tensile force prediction model, the applicability of the proposed method in more than two materials, and the influence of CHLC transformation operation on the improved bat algorithm and neural network are also discussed. [ABSTRACT FROM AUTHOR]

Parametric signal representation techniques with Chirplet models have attracted much attention in ultrasonic guided waves-based research of material property identification and structural integrity evaluation. The known Chirplet models are established using either the Gaussian windows or the linear chirp function. This is inconsistent with practical situations where the excitation is a Hanning-windowed sinusoidal signal, and the received signals have a nonlinear phase and asymmetric envelope due to the dispersive nature of the waves. A nonlinear Hanning-windowed Chirplet (NHWC) model was proposed to eliminate the above inconsistencies in which a nonlinear phase modulation term was designed to modulate the classical Hanning-window and the sine function. The phase modulation term was established with the hyperbolic tangent function. The mathematical properties of the nonlinear phase modulation term and the NHWC model were analyzed mathematically, including the time variability, parity, concavity, and convexity of the phase. These were used to guide the parameter setting in parametric signal representation techniques. The NHWC model can characterize various characteristics of guided waves signals, including the symmetric or asymmetric Hanning envelopes and the phase nonlinearity. Finally, an adaptive genetic algorithm was adopted to verify the effectiveness of the NHWC model in the parameter representation of experimentally measured ultrasonic signals. [ABSTRACT FROM AUTHOR]

To improve the efficiency and robustness of electromagnetic ultrasonic testing, magneto-acoustic compound inspection for ferromagnetic materials is proposed. Both ultrasonic waves and pulsed eddy current (PEC) could be obtained by the single detection of an electromagnetic acoustic transducer (EMAT), where ultrasonic waves were generated based on the coupling of the magnetostriction effect and the Lorentz force mechanism, when the EMAT was used to detect ferromagnetic materials. In this study, three simulation models of the EMAT were built by coupling different physics fields while keeping the geometry of the models unchanged and the other parameters of the EMAT constant. Transverse wave could be generated by magnetostriction force, and longitudinal wave could be generated by Lorentz force. Based on time-frequency analysis of the simulation results, the energies of ultrasonic waves and PEC were concentrated in different frequency ranges. Through the filtering strategy and by separating the time-domain signal, magnetostriction force ultrasonic wave (MFUW), Lorentz force ultrasonic wave (LFUW), and PEC could be decoupled from the EMAT testing signal. Multiple parameters can be extracted by a single detection of the EMAT, and the ability of the electromagnetic ultrasonic testing can be improved. [ABSTRACT FROM AUTHOR]

Assessing the effect of defect induced stresses on magnetic flux leakage (MFL) signals is a complicated task due to nonlinear magnetomechanical coupling. To facilitate the analysis, a multi-physics finite elemental simulation model is proposed based on magnetomechanical theory. The model works by quasi-statically computing the stress distribution in the specimen, which is then inherited to solve the nonlinear magnetic problem dynamically. The converged solution allows identification and extraction of the MFL signal induced by the defect along the sensor scanning line. Experiments are conducted on an AISI 1045 steel specimen, i.e. a dog-bone shaped rod with a cylindrical square-notch defect. The experiments confirm the validity of the proposed model that predicted a linear dependency of the peak-to-peak amplitude of the normalized MFL signal on applied stress. Besides identifying the effect of stress on the induced MFL signal, the proposed model is also suitable for solving the inverse problem of sizing the defects when stress is involved. [ABSTRACT FROM AUTHOR]

Excitation parameter preferences are key factors affecting the performance of magnetic frequency mixing detection. A uniform experimental design method was used to analyze this influence. Using fuzzy theory, a comprehensive model is established for evaluating the effect of magnetic frequency mixing. A polynomial is selected as the regression function to express explicitly the correlation between the excitation parameters and the frequency-mixing effect. The excitation parameters were then optimized using genetic algorithm. Magnetic frequency mixing experiments were conducted to measure the surface hardness of some ferromagnetic materials. Frequency mixing is further enhanced under the optimal settings, resulting in an improvement in the measurement sensitivity. The results of this study support the application of the magnetic frequency mixing technique in non-destructive testing. [ABSTRACT FROM AUTHOR]

Electromagnetic acoustic transducers (EMATs) have been widely applied in nondestructive testings and structural health monitoring. This paper proposes a flexible surface wave electromagnetic acoustic transducer (FSW-EMAT), which uses flexible rubber magnets instead of hard permanent magnets, in order to achieve the defects detection of steel pipe or other ferromagnetic structures with a certain surface curvature. Traditional EMATs mainly consist of three parts: magnet, coil and metal specimen to be tested. Permanent magnets or electromagnets are generally used to produce the strong magnetic flux density. However, the two kinds of magnets are not suitable for the defect detection of metal specimens with a certain curvature. The proposed FSW-EMAT in this paper adopts a flexible magnet, which is a mixture of rubber and iron powder and has strong flexibility to fit the bent specimen. The proposed FSW-EMAT can be easily applied in the testing of curved structural component and detect axial and circumferential defects by rotating the transducer. [ABSTRACT FROM AUTHOR]

Ising model is a promising tool for predicting magnetic Barkhausen noise (MBN) signal on electromagnetic nondestructive evaluation (ENDE). However, theoretical prediction of MBN of composite ferromagnetic materials using Ising model is seldom reported. In this study, we incorporate double Boltzmann transition function with the exchange coupling efficiency (J) of Ising model to achieve simulation of MBN in layered materials. The transition behavior of J was assumed to represent the changes in magnetic properties from hard layer to soft layer. Monte Carlo algorithm is used to solve the Ising model to obtain the MBN of layered material. The influence of the volume fraction (p) of hard layer in the double Boltzmann transition function on the shape of MBN profiles was investigated through both simulation and experiments. In the experiments, two-layer ferromagnetic materials was laminated using SAE 1065 carbon steel films of different thickness and a base strip of SAE 1045 carbon steel with a thickness of 20 mm. Both simulation and experimental results show that the MBN peak of soft layer gradually descends with the increase in thickness of SAE 1065 (or the volume fraction of hard layer). The second-order Gaussian function was used to fit the MBN envelop for extract the peaks of hard and soft layers from both experimental and simulation results. The ratio of the MBN peak of hard layer to soft layer demonstrates monotonously increasing trend as the value of p increases. Therefore, ratio of the MBN peak can act as good indicator for qualitative characterization of the changes of thickness or volume fraction of hard layer in two-layer ferromagnetic materials. [ABSTRACT FROM AUTHOR]

Crack detection is important in the quality control of silicon-based solar cells (SSC). Silicon wafers are semi-conductive and cracks disturb the local conductivity and even induce anisotropy in conductivity of SSC. Eddy current method, which can detect the change of conductivity in the material, is a potential tool for detecting cracks in SSC. In this study, an experimental set-up is proposed to conduct both eddy current O-scan and C-scan imaging to the SSC. The eddy current O-scan was firstly used to investigate the anisotropy in the conductivity of SSC. Through comparing the inherent and crack-induced anisotropy in impedance (amplitude ratio and phase lag), macrocracks could be detected. The changes in the measured directional impedance could roughly reflect the shape of the cross-type macrocrack. In the C-scan mode, multiple slit defects were prepared to simulate macrocracks. Though the lateral resolution of the sensor was limited, the crack detection ability of the sensor could be evaluated with the C-scan imaging results. A slit defect with a width of 0.5 mm and a length of 1 mm was detected. A new criteria, the distance between feature zero-crossing points in the first derivative of the phase lag curve accurately reflected the actual length of the slit. [ABSTRACT FROM AUTHOR]

In the study, ultrasonic longitudinal mode guided waves were employed to detect defects in elbowed tubes (without welds) with a diameter of 10 mm. Finite element simulation results highlighted that the emitted L(0,1) mode guided waves experienced strong reflection and mode conversion at the elbow region to generate F(1,1) mode, followed by slow and weak F(2,1) mode. The guided wave reflected from the elbow with a through-wall defect was manifested as two overlapped wave packets, which were good indicators of a defective elbow. To conduct L(0,1) mode guided waves inspection on the small-diameter elbowed tubes, a novel tailored squirrel-cage magnetostrictive sensor was employed in the experiment. The new sensor employed the configuration of segmental iron-cobalt strips and small-size permanent magnet arrays. The entire sensor is composed of two identical C-shaped sensor elements and can be recycled and installed conveniently. Experimental results obtained from healthy and defective tubes were consistent with the conclusions obtained from finite element simulations. An artificial through-wall defect at the elbow and a notch defect at the straight part of the tube could be simultaneously detected by L(0,1) mode guided waves through comparing experimental signals with simulation results. [ABSTRACT FROM AUTHOR]

Pulse elasto-magnetic method has numerous applications for monitoring cable tension force in cable-stayed bridges. In conventional pulse elasto-magnetic measurements, the feature parameters in frequency domain are seldom discussed. In this study, attempts are made to seek new parameters in frequency domain which are mainly influenced by cable tension force and less sensitive to temperature. A custom-developed pulse elasto-magnetic instrument is employed to conduct cable tension monitoring in the construction stage of a cable-stayed bridge. The field testing results show that only after temperature compensation, the monitoring results of the feature parameters extracted from the magnetic characteristic curve can reflect the stepped changes of cable tension force. Surprisingly, a new frequency-domain parameter, the summation of spectra amplitudes in a carefully selected frequency range, is found to be insensitive to temperature and can well reflect the stepped change behavior of cable tension force. The feasibility of this temperature-insensitive parameter for cable force measurements was verified by field test in two stay cables. The averaged value of the new parameter at each stage linearly depends on cable tension force. The findings about the new frequency-domain parameter may facilitate temperature-insensitive cable tension monitoring in cable-stayed bridge with a pulse elasto-magnetic instrument. [ABSTRACT FROM AUTHOR]

Austenitic stainless steels are widely used in the key components of major equipment and the welds can be the weakest parts of equipment made with these materials. Ultrasonic waves propagate in austenitic stainless steel welds with multiple paths and modes. This study employed a multi-view total focusing method using an ultrasonic phased array for defect detection in the welds of small-diameter austenitic stainless steel pipes. The detection capability of four different direct wave modes and eight different half-skip wave modes for typical defects were compared and analysed through numerical simulation. A fusion imaging method was developed using the preferred direct and half-skip wave modes. The process was further verified with a weld defect detection experiment carried out on small-diameter austenitic stainless steel pipes. The results show that the multi-view total focusing method can efficiently detect the defects in the welds of small-diameter tubes. Compared with the single-mode imaging method, the fusion total focusing imaging approach can not only improve the signal-to-noise ratio but can also reduce the number of image artefacts. [ABSTRACT FROM AUTHOR]

Ultrasonic tomography (UT) is a nondestructive technique that is widely applied in industrial process imaging. In this paper, a novel sector diffusion method for construction of a sensitivity matrix is proposed to improve the performance of a linear back-projection (LBP) algorithm. The so-called sector-diffusion-matrix-based LBP (SLBP) was applied to reconstruct gas/liquid two-phase flow. A series of models has been established to evaluate the effectiveness of the method. The images reconstructed by traditional LBP and SLBP are presented and compared. Two quantitative evaluation criteria including position error and image correlation coefficient ($I_{\mathrm {cr}}$) were defined and used to evaluate the quality of the reconstructed images. The imaging results indicate that the SLBP method is valid and feasible to improve the quality of reconstructed images, especially for a UT system with a small number of transducers. The evaluation criterion $I_{\mathrm {cr}}$ is improved by 26%, 20%, 9%, and 4% for four different flow patterns with an eight-transducer UT system in $128\times128$ pixels and improved by 26%, 20%, 10%, and 1% in $40\times40$ resolution. [ABSTRACT FROM AUTHOR]

In metallic plate structures, a lamination defect is a type of internal defect that is commonly generated in the manufacturing process, which is mostly parallel to the surface of the plate. This study presents a technique of imaging a lamination defect in a metallic plate by using Lamb waves based on the local wavenumber domain analysis method. Owing to the processing technique, an aluminum beam structure is utilized to represent the metallic plate for the detection of the lamination defect. A three-dimensional finite-element model of an aluminum beam with a rectangular lamination defect is constructed with MatLab and ABAQUS commercial software. The propagation characteristics of Lamb waves are discussed by analyzing the simulated wavefield. A complicated wave-propagation phenomenon of multiple reflection and transmission is observed between the interaction of Lamb waves and the lamination. By performing local wavenumber domain analysis on the wavefield, the wavenumber distribution is obtained, from which the location and profile of the lamination defect are identified. An experimental study is carried out to verify the numerical result. A fully non-contact detection system consisting of an electromagnetic acoustic transducer and laser ultrasonic inspection system is established to inspect the artificial machined beam structure. The experimental result is in good agreement with the numerical result. [ABSTRACT FROM AUTHOR]

With the non-dispersion characteristics, the lowest shear horizontal mode SH0 can be widely applied in the detection and monitoring of a defect in plate structures. In order to achieve SH0 mode excitation in aluminum plates, based on Lorentz force mechanism, a new directional SH0 mode EMAT based on periodic grating coil (PGC), called PGC-EMAT, is designed in the study. On the surface of the aluminum plate, the PGC produces the horizontal eddy current. The oppositely induced eddy currents are generated by the adjacent grating units. The current I of the multiple wires in each grating unit is the same. The rectangular magnet provides the static magnetic field perpendicular to the surface of the aluminum plate. In addition, the PGC-EMAT with different grating units of the periodic grating coil and coil layers are simulated by three-dimensional finite element simulation. The simulation results show that with the increase of grating units of the periodic grating coil, the tangential displacement of PGC-EMAT will increase, and the tangential displacement of double-layer periodic grating coil is larger than that of single-layer periodic grating coil when the number of grating units of the periodic grating coil is the same. The developed EMAT can excite and receive a single SH0 mode and the actual center frequency of the transducer coincides with the theoretical value. It was proved that the central frequency of the transducer was controlled by the distance between the adjacent grating units of the periodic grating coil. In order to increase the energy of the signals excited or received by PGC-EMAT, the number of cycles of grating units and the number of layers of the transducer were studied. The experimental results showed that there was a linear relationship between the number of cycles of the grating units and the energy of the excited and received signals. The energy of the excited and received signals of the double-layer PGC-EMAT was larger than that of the single-layer PGC-EMAT when PGC-EMAT was used as excitation transducer or receiving transducer. The simulation results were experimentally verified. The developed PGC-EMAT can be applied in defect detection. [ABSTRACT FROM AUTHOR]

Abstract: Lamb waves defect detection technique is suitable to detect long-range defects and multi-defects in plates because of its attractive properties such as multi-modes, low attenuation, and multi-defect sensitivity. As the laser beams have the tiny size and noncontact property, in this paper a full non-contact laser-based Lamb waves phased array inspection technique was proposed for defect detection in an aluminum plate. A Q-switched Nd: YAG pulse laser generating Lamb waves and a continuous laser inspection system was used to inspect the out-of-plane displacements. The laser-generated Lamb waves have the broadband property and low temporal resolution that are not suitable for defects detection directly. So the continuous wavelet transform was used to extract narrowband signals from laser-generated Lamb wave and a linear mapping algorithm was adopted to compensate for the dispersion of the extracted narrowband signals. Two experiments were carried out to verify the applicability and effectiveness of the developed full non-contact laser-based Lamb waves phased array inspection technique. Two compact phased array imaging algorithms, the total focusing method and the sign coherence factor algorithm, were adopted to image the defects with processed signals. The experimental results accurately located the positions of the defects.Graphical Abstract: [ABSTRACT FROM AUTHOR]