202 results about "Lamb waves" patented technology

The invention provides an aero-engine blade damage detection method based on an improved ultrasonic sparse reconstruction algorithm, and relates to the technical field of aero-engine damage detection positioning, and the method comprises the steps: S1, setting a sensor array and a detection region of a to-be-detected blade, and obtaining an actual measurement damage reflection signal dictionary through a sensor; s2, wave number distribution of a detection area is determined according to a variable thickness structure Lamb wave propagation model, signal reconstruction is carried out, and a theoretical damage reflection signal dictionary is obtained; s3, an aero-engine blade damage detection model is constructed, an improved sparse reconstruction algorithm is adopted to solve and optimize, and damage judgment is carried out; and S4, according to the pixel value distribution condition of the aero-engine blade detection area, generating an aero-engine blade damage detection image, and positioning a damage position. According to the method, the reflected wave amplitude information can be obtained from the array sensor signals, and the reflected wave amplitude information is compared with the reconstructed theoretical reflected signals, so that the damage condition of the aero-engine blade is identified and positioned.

The invention discloses a sheet metal thickness measurement method based on a hybrid system zero group velocity Lamb wave technology, and belongs to the field of nondestructive testing and evaluation.The method comprises the following steps that a hybrid detection system is built, and an out-of-plane displacement vibration signal of a sheet metal is obtained based on the hybrid detection system; converting the out-of-plane displacement vibration signal into a frequency domain signal through fast Fourier transform, and extracting a resonant frequency corresponding to a formant of a zero group velocity Lamb wave mode in the frequency domain signal; calculating a frequency-thickness product based on material parameters of the metal plate; and based on the frequency thickness product, the resonant frequency and a pre-established frequency thickness product-thickness function relationship, performing inversion to obtain a thickness value of the metal plate.

The invention discloses an S0 Lamb wave scattering sound field solving method based on physical constraint enhanced TransUNet. The method comprises the following steps: acquiring a global scattering sound field in an out-of-plane direction after an S0 Lamb wave passes through an irregular defect; performing data processing on the global scattering sound field, and establishing a scattering sound field data set; constructing an S0 Lamb wave scattering sound field prediction model adopting a TransUNet network, dividing a scattering sound field data set into a training set and a test set, and sequentially performing data driving training and physical constraint training on the S0 Lamb wave scattering sound field prediction model by utilizing the training set until training is completed; and inputting thickness distribution of a to-be-tested plate structure containing defects in the test set into the trained S0 Lamb wave scattering sound field prediction model to obtain a predicted scattering sound field with irregular defects, further obtaining a scattering time domain signal and a scattering far field amplitude result, and completing solving of the scattering sound field of the S0 Lamb waves. The invention provides an innovative method for solving the scattering sound field of the irregular defect S0 Lamb wave in the plate.

The invention belongs to the field of train structure health monitoring, and discloses a bogie tube plate structure welding seam detection method and device, and the method comprises the steps: obtaining a Lamb wave signal of a to-be-detected tube plate structure welding seam region, and carrying out the preprocessing, and obtaining a preprocessed Lamb wave signal; on the basis of the preprocessed Lamb wave signal, the position of the weld crack defect of the to-be-detected tube plate structure is predicted through the RAPID tomography technology, and a weld crack defect positioning detection result is obtained; inputting the preprocessed Lamb wave signal sequence into a bogie tube plate structure welding seam detection model to obtain a welding seam crack defect quantitative detection result; outputting a welding seam crack defect positioning detection result and a quantitative detection result as welding seam detection results; according to the invention, the positioning and quantitative detection result of the welding seam damage of the bogie tube plate structure can be quickly and accurately obtained, the high-precision detection requirement of the welding seam of the bogie tube plate structure is met, and the safe operation of a rail transit vehicle is ensured.

The invention discloses an elastomer layer carbon fiber composite material damage positioning method based on elliptic probability fusion, which comprises the following steps: taking different sensors as excitation sources, and collecting Lamb wave signals of a plurality of sensing paths; performing continuous wavelet transform by using a complex Morlet wavelet, and extracting actually measured flight time; introducing a layered wave velocity correction model to optimize an elliptical orbit method, and calculating theoretical flight time and damage probability; introducing a dynamic short-axis optimization model to optimize a probability weighting method, and calculating a damage probability; generating prior distribution by using results calculated by an elliptical orbit method and a probability weighting method; constructing a likelihood function based on the difference between the actually measured flight time and the theoretical flight time; the posterior distribution of the damage position is obtained through the Bayesian theorem in combination with the prior distribution and the likelihood function; sampling the posterior distribution by using an adaptive MCMC algorithm, and generating a probability cloud picture of the damage position; and outputting a final imaging result of the damage position, and positioning the damage position.

The invention provides a stress and temperature detection method based on a multi-angle Lamb wave acoustic elastic effect, and belongs to the technical field of nondestructive detection.The method comprises the steps that a Lamb wave group velocity variation approximate model is built based on the influence of loading stress and temperature on the sample size; based on the acoustic elastic effect, a Lamb wave group velocity variation detection model is constructed; the method comprises the following steps: arranging a preset multi-angle piezoelectric patch based on a preset experimental sample, fixing the experimental sample on a tensile testing machine to obtain a stress experimental system, combining a Lamb wave group velocity variation approximation model to obtain a parameter change condition, verifying a detection model, and performing formula parameter inversion to obtain a stress test result. Solving unknown stress and temperature by using a verified Lamb wave group velocity variation detection model; the method solves the problems that the detection result of the existing stress detection method is greatly fluctuated along with the temperature change, the precision is low, the influence of the stress direction is difficult to accurately calculate, and the temperature influence is neglected.

The invention provides a Lamb wave scattering sound field solving method based on a two-stage Fourier neural operator, and the method comprises the steps: obtaining a scattering sound field of a Lamb wave after the Lamb wave passes through an irregular defect based on the thickness distribution of a plate structure with the irregular defect, and building a data set of the scattering sound field; constructing a prediction model of a Lamb wave scattering sound field; performing first-stage training on the prediction model by using the data set; obtaining a residual sound field by subtracting the real sound field from the obtained first-stage prediction sound field, and carrying out second-stage training on the prediction model; and inputting the thickness distribution of any irregular defect plate structure to be predicted into the first-stage training model, splicing the obtained first-stage prediction sound field and the thickness distribution, inputting the spliced first-stage prediction sound field and the thickness distribution into the second-stage training model to obtain a residual prediction sound field, and adding the first-stage prediction sound field and the residual prediction sound field to obtain a predicted Lamb wave scattering sound field. Through the double-stage labor division mode, the prediction precision and stability are effectively improved.

The invention belongs to the technical field of train safety monitoring, and particularly relates to a damage identification method based on Lamb wave temperature compensation and a related device. The damage identification method comprises the following steps: acquiring a Lamb wave signal and an actual environment temperature of a to-be-detected component; inputting the Lamb wave signal and the actual environment temperature into a pre-constructed Lamb wave temperature compensation network model, and outputting the Lamb wave signal after temperature compensation; and performing damage identification on the to-be-detected component based on the Lamb wave signal after temperature compensation to obtain a damage identification result. After temperature compensation, interference related to temperature is removed, so that damage identification based on the compensated Lamb wave signal is more accurate.

The invention discloses non-contact photoacoustic imaging equipment and method based on leakage Lamb wave detection, in the equipment, a photoacoustic excitation unit excites Lamb waves on the surface of a to-be-detected plate-shaped sample through a photoacoustic effect; the automatic scanning unit drives the to-be-detected plate-shaped sample to move along the scanning direction, so that the two-dimensional full-coverage scanning of the to-be-detected plate-shaped sample by the photoacoustic excitation unit is realized; the signal detection and amplification unit captures the leakage Lamb wave signal and carries out signal amplification; the data acquisition unit acquires the amplified signal in real time and transmits the signal data to the signal processing and imaging end; and the signal processing and imaging end is respectively in communication connection with the photoacoustic excitation unit, the automatic scanning unit and the data acquisition unit, and performs signal acquisition, storage, analysis and imaging processing. The photoacoustic effect excitation technology, the high-sensitivity signal detection technology and the automatic scanning imaging technology are fused, and efficient, accurate and non-contact detection of the surface and subsurface defects of the plate-shaped material is achieved.

The invention discloses an engineering material structure micro-damage detection method based on broadband nonlinear Lamb waves. The engineering material structure micro-damage detection method comprises the steps that an active Lamb wave excitation device and a sensor are arranged on an engineering material structure; driving the active Lamb wave excitation device to generate broadband excitation with a preset bandwidth, and collecting a response signal of the broadband excitation through a sensor; extracting a fundamental wave and a second harmonic from the response signal, the second harmonic representing a nonlinearity of a response of the broadband excitation generated by the micro-damage, the nonlinearity being a contact acoustic nonlinearity caused by the micro-damage under the broadband excitation; and analyzing the response signal by a non-linearity indicator to quantify the non-linearity. According to the method, the micro-crack damage in the aluminum alloy sheet is detected by using the broadband nonlinear Lamb wave, and the method is effective in the aspect of high-sensitivity damage identification. The invention further discloses a corresponding device.

The invention discloses a GDMD Lamb wave structure nondestructive testing method for rapid scanning, and relates to the technical field of Lamb wave structure nondestructive testing, and the method specifically comprises the steps: 1, collecting low signal-to-noise ratio Lamb wave excitation echo data, carrying out the analysis of the collected signal in a frequency domain, and obtaining a GDMD Lamb wave structure nondestructive testing result; the method comprises the following steps of 1, setting a signal decomposition process, 2, setting an initial group delay curve of each Lamb wave mode, and carrying out iteration by adopting a GDMD algorithm, and 3, analyzing each decomposed component mode, extracting a defect echo mode, and further carrying out time delay analysis to determine a defect position. By fitting and compensating dispersion characteristics of different modes, accurate separation of the modes is achieved, even under the conditions that frequencies of the different modes are overlapped and the signal-to-noise ratio is extremely low, defect echoes can be effectively extracted, and dependence of a traditional filtering method on prior statistical characteristics is avoided.

The invention relates to the technical field of structural health monitoring, and particularly provides a damage positioning method based on Lamb wave temperature compensation. The method comprises the following steps: building a structure health monitoring system based on Lamb waves, and grouping sensing paths in a monitoring area; healthy Lamb wave signals at the reference temperature are collected and grouped, reference signals are obtained, and a reference mapping matrix is constructed; the damage Lamb wave signals at the target temperature are collected and grouped, target signals are obtained, and a target mapping matrix is constructed; determining a damage scattering signal at the target temperature; extracting a damage position feature, calculating a path damage probability, and determining a damage position; in the damage positioning process, the method reduces the dependence of Lamb waves on the temperature, realizes the rapid and synchronous positioning of the damage position, and improves the wide applicability.

The invention discloses a plate structure defect Lamb wave full waveform inversion method based on U-Net neural network regularization, and belongs to the field of nondestructive testing. Firstly, a two-dimensional sound wave equation is solved through a frequency domain finite difference method, and analog signals of all receiving points are obtained; the method comprises the following steps: constructing a target function to represent a relative deviation between an analog signal and a sensor actual measurement signal, and converting an inversion problem of defects in a metal plate into an optimization problem of the target function; performing derivation on the target function by using an adjoint state method to obtain a gradient, updating the velocity field along the negative direction of the gradient, and performing regularization processing on the velocity field through a specific coding-decoding structure of the U-Net neural network to suppress noise and artifacts; a frequency serial inversion strategy is adopted, and inversion is carried out step by step from low frequency to high frequency. According to the method, artifacts in the inversion process are suppressed by using the U-Net neural network, dependence of inversion on initial model precision is reduced by using a frequency domain serial inversion strategy, and high-precision inversion of plate structure defects is realized.

The invention provides a round hole damage detection method based on Lamb waves and deep learning. The method comprises the following steps: acquiring an ultrasonic guided wave frequency dispersion curve of a to-be-detected plate; arranging a plurality of acquisition sensors and excitation sensors in the damaged area of the plate; s0 modal Lamb wave excitation signals are symmetrically emitted on the upper surface and the lower surface of the plate through the excitation sensor; receiving a damage scattering signal of the plate through the acquisition sensor; training a neural network model based on the damage scattering signal; and detecting the coordinates and radius of the damage of the circular hole in the plate through the neural network model. According to the method, the linear Lamb wave detection technology is combined with deep learning, features can be extracted and analyzed from complex Lamb wave signals, and damage can be identified and positioned.

The invention relates to a Lamb wave frequency dispersion characteristic sparse reconstruction method based on non-convex optimization, and belongs to the technical field of high-end equipment perception and test.The method comprises the steps that excitation is conducted on a U-shaped suspension arm, and time domain sampling signals at the junction of a U-shaped suspension arm structure are obtained; the time domain sampling signals are preprocessed; constructing a non-convex sparse frequency dispersion curve estimation model based on the preprocessed signal; and converting the non-convex sparse frequency dispersion curve estimation model into an optimization problem, searching a convex preserving condition of a target function, selecting a forward and backward splitting algorithm for solving, obtaining frequency-wave number distribution, and further extracting a frequency dispersion curve. The method solves the problems that a traditional convex regularization method is limited in induction sparse capability and underestimates signal amplitude. Through a non-convex optimization method, the purpose of accurate estimation of the frequency dispersion curve based on fewer measurement points is achieved.

A method and system acoustic logging operations. The method may comprise selecting a transmitter to a casing offset for logging operations, wherein the transmitter is disposed on a logging tool, insonifying at least a part of a casing with the transmitter at an angle of incidence and collecting one or more waveforms with an array of receivers disposed on the logging tool. The method may further comprise identifying one or more wave mode travel times from the one or more waveforms, selecting one or more wavelets from the one or more waveforms, and identifying an attenuation of a lamb wave mode based at least in part on the one or more wave mode travel times and the one or more wavelets.

The invention relates to the technical field of solid plate defect detection, in particular to a solid plate defect detection method based on Lamb wave end face echoes, which comprises the following steps: exciting and receiving wedge piezoelectric transducers are arranged on the same side of a solid plate, exciting and receiving a single-mode Lamb wave signal, and acquiring a multi-path signal comprising a direct wave, a side face echo and a defect reflection echo; by analyzing the difference between a direct wave and a side echo, a defect reflection signal is extracted, and by combining the time difference between the defect reflection signal and the side echo and the Lamb wave propagation speed, a geometric model is established, and the defect position is accurately calculated. By adjusting the position of a transducer, the time difference between a defect reflected wave and a direct wave is constant, a defect echo amplitude value is obtained under the equal propagation condition and compared with a standard test block amplitude value, a mapping relation between the amplitude value and the size is constructed, and accurate quantification of the defect size is achieved.

A device includes a stack of at least two piezoelectric layers configured to propagate a Lamb wave in a mode having an order corresponding to a number of piezoelectric layers of the stack. The stack includes a first piezoelectric layer and a second piezoelectric layer disposed on the first piezoelectric layer. The first piezoelectric layer has a first cut plane orientation, and the second piezoelectric layer has a second cut plane orientation complementary to the first cut plane orientation. The device further includes an interdigitated transducer (IDT) disposed on at least a top surface of the stack or a bottom surface of the stack. In some embodiments, the device is an acoustic resonator. In some embodiments, the device is an acoustic delay line.

The application discloses a manufacturing method of a resonant filter. The method comprises the following steps: manufacturing a first substrate and a resonant filter structure, wherein the resonant filter structure is formed on a first side of the first substrate, the resonant filter structure comprises a bulk acoustic wave resonant structure and a Lamb wave resonant structure, the bulk acoustic wave resonant structure and the Lamb wave resonant structure are electrically connected, the bulk acoustic wave resonant structure comprises a first electrode structure, the Lamb wave resonant structure comprises a second electrode structure, the second electrode structure comprises a first interdigital electrode and a second interdigital electrode, the first electrode structure and the second electrode structure share a same first electrode layer, the first interdigital electrode is electrically connected with the outside, and the second interdigital electrode is electrically connected with the first electrode structure.

The present invention relates to a closed crack imaging device and method based on nonlinear Lamb waves. A measurement system is constructed using a signal generator, a high-voltage amplifier, an excitation probe, a receiving probe, a voltage amplifier, and an oscilloscope. A linear sensor array is established to record the reflection of the Lamb wave on the structure to be measured. The received signal is decomposed using a "db8" wavelet to obtain a harmonic component of the excitation signal at the second harmonic frequency, i.e., the second harmonic, as the nonlinear Lamb wave reflected by the closed crack. The Hilbert transform value of the nonlinear Lamb wave is associated with the pixel value of a given point on the structure to generate a damage image, in which the position of the closed crack is displayed at a position with a higher pixel value. The present invention can promptly detect closed cracks in the structure to be measured, and is of great significance for detecting structural fatigue and corrosion and providing early warning of structural failure and damage.

The invention relates to the technical field of feature compression, in particular to a CFRP wing skin damage feature efficient compression method based on functional principal component analysis. Comprising the following steps that S1, sensor signal data of the CFRP wing skin are obtained, and the sensor signal data comprise Lamb wave signals collected by a plurality of sensors at different damage positions; s2, preprocessing the sensor signal to obtain processed high-dimensional time sequence characteristic data; s3, function type principal component analysis compression processing is carried out on the high-dimensional time sequence feature data, the S3 comprises the following steps: S4, significant time points are screened according to the comprehensive scores, and the S4 comprises the following steps: S5, compressed damage feature data are output, the compressed damage feature data only comprise feature values corresponding to the significant time points, and the feature values only comprise feature values corresponding to the significant time points. The method is used for subsequent damage positioning tasks.

Provided in the present invention are a Lamb wave resonator and a filter, which improve the matching performance of acoustic impedance by means of adjusting and controlling local thin film thickness. Providing recesses in a piezoelectric thin film in first material areas, or forming a dielectric layer below a piezoelectric thin film in second material areas achieves local thickness adjustment for a Lamb wave resonator constituted by interdigital electrodes and having a thickness difference, such that the first material areas and the second material areas are offset with respect to each other in the thickness direction, thus suppressing a stray mode of the Lamb wave resonator; and the response filter is constructed on the basis of the resonator, so as to suppress the phenomenon of passband performance deterioration caused by the stray mode, thereby facilitating development of high-frequency large-bandwidth acoustic resonators.

The invention discloses an aviation aluminum plate wave field image damage monitoring method based on non-convex total variation regularization RPCA. The method comprises the following steps: acquiring Lamb wave field image data of a to-be-detected aviation aluminum plate by using a sensor array; decomposing the mapped Lamb wave field image data by using a non-convex total variation regularization robust principal component analysis algorithm, and solving sub-problems by using an alternating direction multiplier method to obtain a low-rank matrix representing background wave field information and a sparse matrix representing damage abnormal values; performing post-processing including sparse response normalization processing, adaptive threshold segmentation, connected region filtering and morphological repair on the sparse matrix to extract a damaged region; according to the extracted damage area, the damage condition of the aviation aluminum plate to be detected is evaluated and positioned. According to the invention, the accuracy and real-time performance of damage identification can be improved.

The present invention discloses a method for damage identification and assessment of composite wall panels based on Lamb waves and autoencoders. The method comprises: placing a Lamb wave signal acquisition system on a healthy first wall panel and training a deep autoencoder model at each receiver; using the Lamb wave signal acquisition system to acquire Lamb wave response signals for a second wall panel to be inspected; determining the Lamb wave flight time at each receiver on the second wall panel using differential signals; constructing and solving a set of geometric model equations based on a Lamb wave isotropic propagation velocity distribution model to locate the damage position in the second wall panel; and reconstructing the Lamb wave response signals acquired by multiple receivers on the second wall panel using a deep autoencoder model and performing normalization processing to obtain a final comprehensive damage assessment score. The method has the advantages of high positioning accuracy, strong assessment sensitivity, and good ability to distinguish damage levels, and is suitable for nondestructive testing and assessment of composite structural wall panels.

The invention belongs to the technical field of metal plate damage detection, and particularly relates to a Lamb wave damage imaging method based on linear prediction. According to the method, a Lamb wave damage imaging signal model is adopted, a linear prediction technology is combined, and high-precision damage imaging is carried out; comprising the steps that a linear uniform sensor array (ULA) in a Lamb wave damage imaging signal model is virtually expanded through a linear prediction technology, a virtual linear array with a large aperture is obtained, and therefore the resolution ratio of the linear array and the damage imaging precision are improved; in order to solve the problem of model mismatch caused by related noise introduced by linear prediction, an interference and noise covariance matrix is reconstructed by adopting an iterative adaptive method, so that high-quality damage imaging is realized.

The invention provides a Lamb wave benchmark-free damage imaging method based on adaptive clustering and semantic weighting, and belongs to the technical field of air coupling ultrasonic detection.The Lamb wave benchmark-free damage imaging method comprises the steps that a full-path response signal is collected through orthogonal scanning, a wavelet low-frequency approximation coefficient and a normalized symmetric difference factor are extracted to construct a joint feature vector; and performing unsupervised division of'health-damage 'states on a scanning path by adopting DBSCAN clustering. And semantic tags obtained by clustering are further used as adaptive weights to be embedded into the improved RAPID probability imaging model, and dynamic construction of artifact path suppression and soft reference is realized. In a layering defect detection experiment of the carbon fiber reinforced composite material, compared with a traditional RAPID method, the average size measurement error is reduced by 50.5% under the condition that an independent health reference is completely not needed, the measurement precision of 40 * 20 * 0.05 mm defects in the X / Y direction is improved by 81.7%, the measurement precision of 40 * 20 * 0.05 mm defects in the Y / X direction is improved by 65.5%, and meanwhile 92.3% of boundary artifacts are effectively restrained.

An acoustic wave device for suppressing spurious waves in Lamb waves, and a filter including the same, are provided. The acoustic wave device comprises a support substrate; a piezoelectric substrate supported by the support substrate and defining a first resonator region; and a first resonator and a second resonator disposed in the first resonator region, each comprising a plurality of interdigital transducer (IDT) electrodes and electrically connected to each other. The support substrate includes a first cavity formed beneath the first resonator and a second cavity formed beneath the second resonator, wherein the first cavity and the second cavity are interconnected within the support substrate.

A selective acoustic electromagnetic transducer (400) for a Lamb wave propagation mode of interest propagating in a structure, comprising a circularly shaped magnet (401) and a coil (402) comprising several independent concentric circular portions and a processing unit (403) connected to the ends of each circular portion, the processing unit (403) being configured to generate a composite signal equal to a linear combination of the signals measured on each circular portion, the coefficients of the linear combination being chosen so as to minimize the sensitivity of the coil (402) to a set of Lamb modes excluding the mode of interest. Figure 4a

The application discloses a nonlinear Lamb wave excitation deviation evaluation method and system under dispersion constraint, belongs to the technical field of ultrasonic nondestructive testing and structural health monitoring, and is based on a Rayleigh-Lamb frequency equation and a second-order perturbation theory to construct a second harmonic displacement field model, divides a phase velocity matching mode pair into an intersection type, a longitudinal wave type and a cutoff type; the contraction law of a propagation distance and a mode order on an excitation window is quantitatively analyzed, an excitation tolerance coefficient and a relative gain coefficient are introduced, a two-dimensional quantitative evaluation system of mode pairs is established, three typical mode pairs are divided and are adapted to different detection working conditions, and an aluminum alloy sheet experiment is completed to verify the application. The application adopts the above-mentioned nonlinear Lamb wave excitation deviation evaluation method under dispersion constraint, establishes a standardized mode evaluation system, and significantly improves detection sensitivity and engineering reliability.

This invention discloses a nonlinear Lamb wave detection method for micro-damage in plate structures based on a flexible sensor array, belonging to the field of nondestructive testing technology. The method includes: generating a sinusoidal modulated excitation signal using a Hanning window; extracting nonlinear characteristic parameters reflecting micro-damage in the plate structure from the preprocessed signal using time-frequency analysis and empirical mode decomposition algorithms; generating a fused damage probability map based on compressed sensing theory and the extracted nonlinear characteristic parameters; constructing a damage distribution profile in the thickness direction by analyzing the penetration depth differences of Lamb waves at different frequencies; and automatically quantifying and analyzing the identified damage areas to obtain the damage detection results. This invention aims to achieve early identification and precise localization of micro-damage in plate structures, effectively overcoming the shortcomings of low sensitivity and inaccurate localization in traditional detection methods, and significantly improving detection accuracy, efficiency, and automation.