Quantitative Prediction of Surface Hardness in Cr12MoV Steel and S136 Steel with Two Magnetic Barkhausen Noise Feature Extraction Methods.

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.

Micromagnetic and Robust Evaluation of Surface Hardness in Cr12MoV Steel Considering Repeatability of the Instrument.

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.

Surface Decarburization Depth Detection in Rods of 60Si2Mn Steel with Magnetic Barkhausen Noise Technique.

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.

Lamb Waves Propagation Characteristics in Functionally Graded Sandwich Plates.

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.

Evaluation of the Magnetocrystalline Anisotropy of Typical Materials Using MBN Technology.

Magnetic Barkhausen noise (MBN) signals in the stage from saturation to remanence of the hysteresis loop are closely correlated with magnetocrystalline anisotropy energy. MBN events in this stage are related to the nucleation and growth of reverse domains, and mainly affected by the crystallographic textures of materials. This paper aims to explore the angle-dependent magnetocrystalline anisotropy energy. Based on the consideration of macroscopic magnetic anisotropy, with the concept of coordinate transformation, a model was firstly established to simulate the magnetocrystalline anisotropy energy (MCE) of a given material. Secondly, the MBN signals in different directions were tested with a constructed experimental system and the characteristic parameters extracted from the corresponding stage were used to evaluate the magnetic anisotropy of the material. Finally, the microstructures of 4 materials were observed with a metallographic microscope. The microtextures of local areas were measured with the electron backscatter diffraction (EBSD) technique. The MBN experimental results obtained under different detection parameters showed significant differences. The optimal MBN detection parameters suitable for magnetic anisotropy research were determined and the experimental results were consistent with the results of MCE model. The study indicated that MBN technology was applicable to evaluate the MCE of pipeline steel and oriented silicon steel, especially pipeline steel.

Piezoelectric Impact Energy Harvester Based on the Composite Spherical Particle Chain for Self-Powered Sensors.

In this study, a novel piezoelectric energy harvester (PEH) based on the array composite spherical particle chain was constructed and explored in detail through simulation and experimental verification. The power test of the PEH based on array composite particle chains in the self-powered system was realized. Firstly, the model of PEH based on the composite spherical particle chain was constructed to theoretically realize the collection, transformation, and storage of impact energy, and the advantages of a composite particle chain in the field of piezoelectric energy harvesting were verified. Secondly, an experimental system was established to test the performance of the PEH, including the stability of the system under a continuous impact load, the power adjustment under different resistances, and the influence of the number of particle chains on the energy harvesting efficiency. Finally, a self-powered supply system was established with the PEH composed of three composite particle chains to realize the power supply of the microelectronic components. This paper presents a method of collecting impact energy based on particle chain structure, and lays an experimental foundation for the application of a composite particle chain in the field of piezoelectric energy harvesting.

Detection of Single Steel Strand Distribution in Grouting Duct Based on Capacitive Sensing Technique.

Grouting ducts (containing steel strands) are widely used to increase the structural strengths of infrastructures. The determination of the steel strand's integrity inside of ducts and the grouting quality are important for a strength evaluation of the structure. In this study, a capacitive sensing technique was applied to identify the cross-sectional distribution of the steel strands. The distribution was expressed in polar coordinates in an external post-tensioned pre-stressed duct model. An improved capacitive sensor structure was designed, which consisted of four electrodes, and different electrode-pairs were used to determine various locations' information of the steel strands. Two rounds of measurements were conducted using the designed sensor to detect the angle (θ) and center distance (r) of the steel strand in the duct. The simulated and experimental results are presented and analyzed. In general, it is difficult to locate the angle of a steel strand directly from first-round capacitance measurements by analyzing the experimental results. Our method based on Q-factor analysis was presented for the position detection of a steel bar in an external post-tensioned pre-stressed duct. The center distance of the steel bar could be identified by second-round capacitance measurements. The processed results verified the effectiveness of the proposed capacitive sensor structure. Thus, the capacitive sensing technique exhibited potential for steel strand cross-section distribution detection in external post-tensioned pre-stressed ducts.

Development of a Flexible Broadband Rayleigh Waves Comb Transducer with Nonequidistant Comb Interval for Defect Detection of Thick-Walled Pipelines.

It is necessary to develop a transducer that can quickly detect the inner and outer wall defects of thick-walled pipes, in order to ensure the safety of such pipes. In this paper, a flexible broadband Rayleigh-waves comb transducer based on PZT (lead zirconate titanate) for defect detection of thick-walled pipes is studied. The multiple resonant coupling theory is used to expand the transducer broadband and the FEA (Finite Element Analysis) method is used to optimize transducer array element parameters. Optimization results show that the best array element parameters of the transducer are when the transducer array element length is 30 mm, the thickness is 1.2 mm, the width of one end of is 1.5 mm, and the other end is 3 mm. Based on the optimization results, such a transducer was fabricated and its performance was tested. The test results were consistent with the finite-element simulation results, and the -3 dB bandwidth of the transducer reached 417 kHz. Transducer directivity test results show that the Θ-3dB beam width was equal to 10 °, to meet the defect detection requirements. Finally, defects of thick-walled pipes were detected using the transducer. The results showed that the transducer could detect the inner and outer wall defects of thick-walled pipes within the bandwidth.

Measurement of circumferential Lamb waves using a line-focus poly(vinylidene fluoride) transducer and cross correlation waveform analysis.

This paper presents a method for measuring circumferential Lamb waves propagating on a cylindrically curved thin plate. The measurement is carried out using a wideband and line-focused poly(vinylidene fluoride) transducer along with a defocusing waveform measurement method. After synthesizing the acquired waveforms, interference patterns can be obtained and a cross correlation method is developed to accurately extract the wave velocity as a function of wave frequency. Using three stainless steel thin plates of different thicknesses (100, 150, and 300 µm) and a radius of curvature of 10 mm, dispersion curves for several fundamental and higher order modes of circumferential Lamb waves are simultaneously determined. Theoretical dispersion curves are also calculated and compared with their experimental counterparts. Very good agreements are observed, which concludes the measurement accuracy of this measurement method.

Characterization of Bonding Defects in Fiber-Reinforced Polymer-Bonded Structures Based on Ultrasonic Transmission Coefficient.

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.

Laser ultrasonic frequency-domain imaging and phase weighted optimization based on full matrix capture.

Far-field laser technology has greatly promoted the progress of nondestructive ultrasonic imaging of bulk structures. However, under thermoelastic excitation, the body waves exhibit a relatively low signal-to-noise ratio, resulting in images with low resolution and contrast. Based on the motivation, this paper developed a frequency-domain phase weighted imaging method to improve the quality of laser ultrasonic defect imaging. Firstly, laser ultrasonic scanning was performed on the sample with artificial transverse hole defects. The cylindrical lens focused line source was used to improve the intensity of the body wave signals, and ensure that there was no damage on the material surface under high laser energies. Then, the frequency-domain phase shift migration (PSM) algorithm was used to perform multimode imaging of defects, achieving frequency-domain synthetic aperture focusing technique (F-SAFT) and total focused method (F-TFM) imaging based on full matrix capture. Furthermore, the phase circular statistical vector (PCSV) was proposed for weighted optimization, which improved the image quality, suppressed the background noise and multimode artifacts. Finally, the imaging quality of several algorithms were discussed. The results indicate that frequency-domain images were superior to time-domain results. After phase weighting, the imaging quality can be further improved, and the detection blind zone was significantly reduced. This work will contribute to the rapid and high-quality defect imaging of laser ultrasonic.

Ultrasonic reflection characteristics of Lithium-ion battery based on Legendre orthogonal polynomial method.

Mechanical properties such as density and Young's modulus of lithium-ion battery electrodes are related to the state of charge (SOC). Characterizing the battery SOC by means of ultrasonic non-destructive testing can obtain the relationship between wave propagation information and the SOC. During the battery charging process, the Young's modulus and density of the internal electrode material will change, which will affect the propagation of ultrasonic waves in the battery. In this research, a clear and more comprehensive description of the reflection characteristics of ultrasonic waves in lithium-ion batteries have been presented. The Legendre orthogonal polynomial method (LOPM) was first introduced to solve the reflection coefficients of single- and multi-cell lithium-ion batteries. The angular spectrum and frequency spectrum of which were regularly shifted with the SOC, so the SOC could be characterized accordingly. The results obtained by finite element simulation were highly consistent with the method used. Moreover, an ultrasonic reflection experiment system was built, which the result matched with theoretical calculation in a customized battery, further verified the feasibility of the method.

A technique based on nonlinear Hanning-windowed chirplet model and genetic algorithm for parameter estimation of Lamb wave signals.

Parameter estimation techniques based on chirplet models and intelligent algorithms can realize the simultaneous multi-information extraction of signals. They have attracted considerable attention for the processing of Lamb wave signals to detect defects and evaluate the material properties. Influenced by their dispersive nature, Lamb wave signals possess nonlinear instantaneous frequencies and asymmetric envelopes. However, the classical chirplet models are established with either Gaussian windows or linear chirps. They are inadequate for characterizing the dispersion features of ultrasonic signals whose excitations are modulated by Hanning windows. In our previous work, a nonlinear Hanning-windowed chirplet (NHWC) model with nine parameters was proposed to realize the full characterization of waveforms. However, the large number of parameters limits its application. A simple NHWC model with seven parameters was designed by submitting the same nonlinear phase modulation term into the Hanning-windowed sine function in this paper. Furthermore, a real-coded multi-objective genetic algorithm was developed to realize the parameter estimation of signals by combining a clustering algorithm and the NHWC model. Different strategies were adopted to ensure the convergence of the algorithm. The maximum extreme values were adopted to realize adaptive discretization of the search space and the updating of parameters. The parameters in the NHWC models were divided into implicit and explicit parts, and different strategies were applied to update them. The clustering algorithm and a sorting combination method were employed to generate a Pareto set. Experimental results showed that the parameter estimation with the simplified NHWC model exhibited a more robust performance than that of the model that contained nine parameters for characterizing the Lamb wave signals with or without the dispersion features. The arrival time, amplitude, and instantaneous frequencies of wave packets were identified with the parameter estimation technique.

Evolutionary Strategy-Based Location Algorithm for High-Resolution Lamb Wave Defect Detection With Sparse Array.

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.

Full Concentration Gradient-Tailored Li-Rich Layered Oxides for High-Energy Lithium-Ion Batteries.

Lithium-rich layered oxides (LLOs) are prospective cathode materials for next-generation lithium-ion batteries (LIBs), but severe voltage decay and energy attenuation with cycling still hinder their practical applications. Herein, a series of full concentration gradient-tailored agglomerated-sphere LLOs are designed with linearly decreasing Mn and linearly increasing Ni and Co from the particle center to the surface. The gradient-tailored LLOs exhibit noticeably reduced voltage decay, enhanced rate performance, improved cycle stability, and thermal stability. Without any material modifications or electrolyte optimizations, the gradient-tailored LLO with medium-slope shows the best electrochemical performance, with a very low average voltage decay of 0.8 mV per cycle as well as a capacity retention of 88.4% within 200 cycles at 200 mA g-1 . These excellent findings are due to spinel structure suppression, electrochemical stress optimization, and Jahn-Teller effect inhibition. Further investigation shows that the gradient-tailored LLO reduces the thermal release percentage by as much as about 41% when the battery is charged to 4.4 V. This study provides an effective method to suppress the voltage decay of LLOs for further practical utilization in LIBs and also puts forward a bulk-structure design strategy to prepare better electrode materials for different rechargeable batteries.

An improved analytical model of the magnetostriction-based EMAT of SH0 mode guided wave in a ferromagnetic plate.

The accuracy of electro-acoustic energy transfer efficiency (EAETE) model directly determines the optimization results of an electromagnetic acoustic transducer (EMAT). In this study, the EMAT model of SH0 mode generation based on magnetostriction mechanism is re-examined. In the existing magnetostriction-based EMAT (MEMAT) analytical model, an approximate method of dynamic magnetic field was employed. Thus the effects of the tested ferromagnetic materials on the dynamic magnetic field in the air is ignored and the boundary condition between air and material is not exact. As a result, the calculated dynamic magnetic field inside the tested ferromagnetic materials is incorrect, thus leading to the calculation errors of magnetostriction body force and the final EAETE of MEMAT. The rigorous analytical solutions for calculating the dynamic magnetic field are derived based on Maxwell equations and boundary conditions in this study. The prediction results of improved analytical model were consistent with previously reported experimental results. Compared with existing analytical models, the improved model showed the higher prediction accuracy of several parameters, including dynamic magnetic field, magnetostriction force and the EAETE.

Development of a mode-tuning magnetic-concentrator-type electromagnetic acoustic transducer.

In the traditional electromagnetic acoustic transducer (EMAT) based on Lorentz force mechanism, to meet the principle of constructive interference, the coil center distance is generally set to be half of the wavelength of the specified mode. The fixed center-to-center coil produces a Lorentz force under the action of a uniform static magnetic field provided by the magnet, thereby producing a specified mode signal that satisfies the constructive interference. In the above principle, the center distance of the coil is fixed, and applied with a uniform static magnetic field, which the coils with different center distances are combined with the dispersion curve to control the mode of the generated signal; that is, tuning the signal mode by changing the center distance of the coil. Another way to tune the signal mode is by changing the configuration of the magnet. Adopting appropriate waves for the identification of individual types of defects facilitates faster and more accurate detection. When using EMAT, some specifications of EMAT need to be changed, which can be inefficient and costly. To solve the problem, a mode-tuning magnetic-concentrator-type electromagnetic acoustic transducer (MT-MC-EMAT) is proposed in this study. This type of EMAT controls the mode of the generated signal by controlling the center distance of the static magnetic field provided by the magnet; that is, designing a new type of double-layer variable-pitch meander coil and different magnetic concentrators to select each coil. This method can tune the mode of the excitation signal by replacing the magnetic concentrator without changing a series of parameters, such as the coil, magnet, and excitation frequency. Different types of magnetic concentrators were added to a traditional EMAT to guide and concentrate the magnetic field of the permanent magnet, thereby changing the distribution of the magnetic flux density. These magnetic concentrators corresponded to meander coils with different pitches to satisfy constructive interference and achieve signal mode tuning. Both finite element simulation and experiment proved that the mode generated by this transducer was tunable after adding the different types of magnetic concentrators. Furthermore, experiments were conducted to examine the transducer characteristics. Finally, the configuration of the MT-MC-EMAT was optimized through orthogonal experiments. The influence of each parameter on the transducer efficiency of the proposed MT-MC-EMAT was studied, and the optimal parameter combination was confirmed.

Incremental scattering of the A0 Lamb wave mode from a notch emanating from a through-hole.

Lamb wave scattering from a crack originating at a through-hole is of practical importance because of the abundance of fastener holes used in engineering structures. Notches are often used to simulate cracks so that Lamb wave methods can be more conveniently investigated in the laboratory. A linear, three-dimensional finite element model is employed in this paper to study incremental scattering of the fundamental anti-symmetric (A0) Lamb wave mode from notches emanating from through-holes. The term "incremental scattering" refers to the change in scattering caused by introduction of the notch and is motivated by structural health monitoring for which transducers are fixed and signal changes are interpreted to detect damage. Far-field angular scattering patterns are generated for multiple incident angles and frequencies, and such patterns are experimentally validated at one frequency by laser vibrometry measurements. Comparisons are made between a vertical notch alone (no hole) and notches located above and below the through-hole. Additionally, holes of different sizes are considered to investigate the effect of hole diameter on incremental scattering patterns. Results show that the presence, location and size of the through-hole affect both the shape and strength of notch incremental scattering patterns.

Modeling guided wave propagation in functionally graded plates by state-vector formalism and the Legendre polynomial method.

A numerical method is presented for the investigation of the propagation characteristic of guided waves in functionally gradient material (FGM) plates. Based on the State-vector formalism and Legendre polynomial method, the typical non-stratified computing of dispersion curves of FGMs is realized, by introducing the univariate nonlinear regression to optimize the arbitrary gradient distribution of material component. Comparing with the conventional Matrix method, the proposed method avoids the exhausting root-locating algorithm of solving the transcendental equation by a single-variable scanning process. This method turns it into an algebraic eigenvalue problem, which mainly depends on the orthogonal completeness and strong recursive property of Legendre polynomial series. It provides a fast and flexible approach to extracting the dispersion curves, displacement distribution and stress profile, simultaneously. Results from chrome-ceramic FGM plate are compared with those from the previous articles to confirm the feasibility and accuracy of the proposed method. Then, this approach is further applied to iron based alumina FGM. The dispersion curves with different gradient function are calculated to illustrate the influence of the gradient variation. Moreover, the influence of the cut-off order of Legendre orthogonal polynomials on the convergence of dispersion curves is also revealed through numerical examples. Utilizing the mapping relationship between the gradient distribution and the propagation characteristics, it gives theoretical support for nondestructive evaluation and quantitative estimation of the structural characteristics of FGM plates.

Observation of ultrasonic guided wave propagation behaviours in pre-stressed multi-wire structures.

Ultrasonic guided wave (UGW) is a promising technique for nondestructive testing of pre-stressed multi-wire structures, such as steel strand and wire rope. The understanding of the propagation behaviours of UGW in these structures is a priority to applications. In the present study, first the properties of the UGW missing frequency band in the pre-stressed seven-wire steel strand is experimentally examined. The high correlation between the observed results and the previously published findings proves the feasibility of the magnetostrictive sensor (MsS) based testing method. The evolution of missing frequency band of UGW in slightly tensioned steel strand is discussed. Two calibration equations representing the relationship between the missing band parameters and the tensile force are given to derive a new tensile force measurement method, which is capable of measuring an incremental of stress of approximately 3MPa. Second, the effects of tensile force on the UGW propagation behaviours in three types of complicated steel wire ropes are alternatively investigated based on the short time Fourier transform (STFT) results of the received direct transmission wave (DTW) signals. The observed inherent missing frequency band of the longitudinal mode UGW in the pre-stressed steel wire rope and its shifting to a higher frequency range as the increases of the applied tensile force are reported for the first time. The influence of applied tensile force on the amplitude of the DTW signal and the unique UGW energy jump behaviour observed in a wire rope of 16.0mm, 6×Fi(29)+IWRC are also investigated, despite the fact that they cannot yet be explained.