168 results about "Laser ultrasonics" patented technology

The invention discloses a detection method and device for intelligent visual detection of parts and a storage medium, belongs to the technical field of industrial quality detection, and aims to solve the problems that surface and internal defects of complex parts are difficult to identify synchronously and the identification precision is low. The method comprises the following steps: acquiring multi-modal image data obtained through structured light three-dimensional imaging and laser ultrasonic scanning; performing geometric registration and scale normalization on the image to generate a fused image; carrying out image preprocessing and edge analysis, and extracting a region of interest; dividing the candidate region of interest into a plurality of image blocks, and inputting the image blocks into an anomaly detection network; calculating a reconstruction error between the original image block and the reconstructed image block, and generating an abnormal scoring graph; and finally, extracting a defect area through image post-processing, and outputting information such as a defect type, a spatial position, a geometric dimension and a severity level. According to the method, the robustness and accuracy of multi-modal defect identification are improved, and the method is suitable for an online visual inspection task of an industrial production line.

The invention discloses a laser ultrasonic defect imaging method based on sampling-imaging double-order compressed sensing, and relates to the technical field of laser ultrasonic detection and material defect detection, and the method comprises the following steps: carrying out sparse scanning on a to-be-detected sample through a random sparse sampling strategy; according to a compressed sensing principle, global ultrasonic intensity distribution of full-matrix scanning under a high sampling rate is reconstructed, and global sparse positioning is realized through extreme value detection; then, on the basis of global sparse positioning, carrying out local fine scanning by adopting high spatial resolution; and generating a sparse imaging result with low spatial resolution by using global sparse positioning and local fine scanning data through a synthetic aperture focusing technology, and performing high-resolution compressed sensing reconstruction imaging by using a compressed sensing principle again. Therefore, by adopting the laser ultrasonic defect imaging method based on sampling-imaging double-order compressed sensing, efficient imaging of tiny defects can be realized, and scanning points are reduced while the imaging precision is improved.

The invention relates to the technical field of ultrasonic signal processing, in particular to a wavelet and MAD adaptive threshold combined laser ultrasonic signal denoising method. The method comprises the following steps: firstly, preprocessing an acquired trigger channel signal and an ultrasonic channel signal, determining a signal starting point through differential positioning, and intercepting an effective signal segment; carrying out multilayer wavelet decomposition on the effective signal segment to obtain a wavelet coefficient of each layer; extracting a detail coefficient of the highest decomposition layer, and adaptively estimating a noise standard deviation based on a median absolute deviation criterion; calculating an adaptive threshold according to the noise standard deviation and the signal length, and processing each layer of wavelet coefficient by adopting a hard threshold function; and finally, carrying out wavelet inverse transformation reconstruction to obtain a denoised signal. According to the method, prior noise information is not needed, the noise level can be adaptively estimated, the optimal threshold value can be determined, the signal features are reserved while noise is effectively suppressed, and the signal-to-noise ratio is remarkably improved.

The utility model provides a four-roll-shaft laser ultrasonic concrete paver, which relates to the technical field of concrete pavers and comprises a laser ultrasonic concrete paver assembly, and a cleaning assembly is arranged in the laser ultrasonic concrete paver assembly. A tamping and paving assembly is arranged on the side face of the laser ultrasonic concrete paver assembly, the laser ultrasonic concrete paver assembly comprises an auger material distribution shaft, a high-speed leveling shaft and a high-frequency vibration shaft, and the tamping and paving assembly comprises a fixing plate; according to the concrete surface rubbing device, the vibration motor works to drive the vibration rubbing plate to vibrate, so that the vibration rubbing plate vibrates and rubs the concrete surface, and tiny low-lying and uneven areas on the concrete surface can be conveniently filled; the undulation and wavy defects caused by insufficient extrusion of the roller shaft in the paving process of the concrete surface are effectively reduced, so that the concrete surface is smoother, the flatness and compactness of the concrete surface are improved, and the pavement quality is further improved.

The invention discloses a heterostructure bonding quality evaluation method and device based on non-contact laser ultrasound. The method comprises the following steps: aiming at a target multi-layer heterostructure, calculating all corresponding resonance modes by utilizing a computer finite element simulation method to obtain a multi-mode theoretical resonance frequency; carrying out laser ultrasonic multi-point scanning on a preset plane area of the target multilayer heterostructure based on a thermoelastic effect by utilizing the established detection device, and collecting an ultrasonic signal; performing time-frequency domain conversion on the ultrasonic signal to obtain a corresponding frequency spectrum signal, and further obtaining a multi-modal measurement resonance frequency; and comparing the multi-mode theoretical resonance frequency with the multi-mode measurement resonance frequency to obtain a heterostructure bonding quality evaluation result. According to the invention, the accuracy of bonding quality evaluation is improved, and the evaluation convenience is improved.

The invention discloses a cable strength detection method and system, relates to the technical field of cable detection, and solves the technical problems that the metal cable detection process is not standard, the defect positioning and quantification precision is low, the contradiction between the non-metal cable detection efficiency and precision is prominent, and microscopic verification is lacked. A high-frequency arc-shaped phased array probe, a bicrystal oblique TOFD probe and an oil-based high-viscosity coupling agent are adopted, a layered focusing technology is combined, laser ultrasonic non-contact detection and ultrasonic microscope high-resolution imaging are adopted for a non-metal cable, and spiral scanning and circumferential fixed-point scanning are combined, so that the defect omission ratio in the circumferential direction is reduced; the abnormal region judgment takes a calibration test block as a reference, the misjudgment rate is reduced, the authenticity is verified through coarse scanning and locking of a core region, fine scanning and acquisition of a high-resolution image and multi-angle imaging, the defect type judgment basis is clear, and the misjudgment rate is reduced.

The invention provides an argon arc welding tungsten electrode appearance defect detection method and system and a storage medium, and relates to the technical field of tungsten electrode appearance detection.The method comprises the steps that firstly, a sample electrode with known defects is subjected to three-dimensional scanning and discretization into a plurality of space points, and each point is endowed with a defect existence mark; by applying a composite sine wave excitation current, an eddy current signal generated when a collector spirally passes through a detection coil at a constant speed is acquired, and laser ultrasonic scanning is synchronously utilized to acquire full-matrix data and reconstruct a three-dimensional gray model. And constructing a double-branch deep learning model, fusing the eddy current feature vector and the ultrasonic image block feature, and learning a mapping relationship between the eddy current feature vector and the defect mark. And performing the same detection on a to-be-detected electrode, outputting the defect confidence of each position by using the trained model, calculating a comprehensive quality index in combination with a preset defect severity weight and a spatial key region weight, and judging whether the electrode is qualified or not according to a qualified threshold value. According to the invention, high-precision, automatic and comprehensive detection of surface and internal defects is realized.

The invention discloses a component defect detection method and device, electronic equipment and a storage medium. The method comprises the following steps: constructing a three-dimensional model of a component; collecting laser ultrasonic data of the three-dimensional model, and collecting a thermal imaging image and a polarized light image of the assembly; based on the laser ultrasonic data, the thermal imaging image and the polarized light image, predicting to obtain a first defect category and a first defect position corresponding to a defect area of the assembly; based on the defect category and the defect position of the defect area, reconstructing three-dimensional defect data of the component; and on the basis of the three-dimensional defect data, predicting to obtain an expansion direction and an expansion range of the defect area.

The invention discloses an automatic grading device for thermal shock cracks of a coating and an application method. Comprising a terahertz wave detection module, a laser ultrasonic excitation and detection module, a high-precision three-dimensional motion control platform, a multi-mode signal synchronous acquisition and processing unit, a crack intelligent grading evaluation unit, an environment simulation and temperature control unit, a protective shell and a human-computer interaction interface. The near-surface dielectric property change of the coating is represented through the terahertz technology, the deep mechanical property evolution is detected through the laser ultrasonic technology, the thermal shock service condition is reproduced in combination with a high-temperature environment simulation unit, and a multi-modal feature fusion algorithm and a physical model and machine learning collaborative inversion model are adopted to obtain the thermal shock resistance of the coating. And automatic quantitative evaluation and severity grading of the depth, density, length and network connectivity of the thermal shock cracks of the thermal barrier coating are realized. The problems that an existing single detection method is insensitive to vertical cracks, poor in high-temperature environment adaptability and low in manual evaluation efficiency are solved.

The invention relates to the field of welding seam detection, and discloses a welding seam center line real-time tracking method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a laser tracking evaluation speed, an ultrasonic tracking evaluation speed and a tracking speed threshold value of a to-be-detected weldment; if the laser tracking evaluation speed and the ultrasonic tracking evaluation speed are both larger than the tracking speed threshold value, the weld joint center line of the to-be-detected weldment is tracked according to a laser and ultrasonic simultaneous inspection strategy; and if the laser tracking evaluation speed or the ultrasonic tracking evaluation speed is smaller than or equal to the tracking speed threshold value, the welding seam center line of the to-be-detected weldment is tracked according to a main laser and auxiliary ultrasonic strategy. According to the invention, the obvious limitation of a single laser tracking technology under the conditions of a complex surface and strong illumination is overcome, and high-precision and high-robustness real-time tracking is realized through acousto-optic fusion.

The invention relates to the technical field of ultrasonic testing, in particular to a titanium alloy bar surface abrasion morphology detection method and system. The method comprises the following steps that non-contact scanning is conducted on the surface of a titanium alloy bar through a preset laser ultrasonic scanning system, a one-dimensional time domain ultrasonic signal is obtained, and the ultrasonic signal is decomposed into a plurality of IMF components; determining a point oscillation duration factor of each signal point in each IMF component; based on time domain window division, calculating an oscillation discreteness index of an oscillation duration factor of each point, and calculating frequency domain sharpness of each IMF component and an original signal; fusing the oscillation discreteness index and the frequency domain sharpness to generate a self-adaptive wavelet threshold parameter, denoising each IMF component by adopting the threshold parameter, and reconstructing to obtain an enhanced ultrasonic signal; and generating a titanium alloy bar surface wear morphology graph. According to the method, the accuracy and robustness of micro-wear detection on the surface of the titanium alloy bar in a high-noise environment are remarkably improved.

The invention provides a laser ultrasonic equipment fixing device for identifying micro-damage on the surface of a high-temperature service pipeline, which comprises an upper bracket and a lower bracket, and openings of the upper bracket and the lower bracket abut against each other and can be mounted on a to-be-detected pipeline. A support locking piece is arranged at the abutting position of the upper support and the lower support to fix the upper support and the lower support together. The upper support and the lower support are each provided with a plurality of pipeline fasteners, and the distance between each pipeline fastener and the outer surface of a to-be-detected pipeline can be independently adjusted. When the device is used, the upper bracket and the lower bracket are fixed on the outer surface of a to-be-detected pipeline by using the bracket locking piece, and the pulse laser and the laser interferometer which are used for detecting the damage of the outer surface of the pipeline are integrated on the upper bracket, so that the whole device is compact in structure and only occupies the peripheral space of the pipeline; and the pulse laser and the laser interferometer are not in direct contact with the high-temperature to-be-measured pipeline, so that the effects that the occupied space is small, the device can adapt to a complex pipeline environment and the service life of equipment is prolonged are achieved.

The invention discloses a W-Cu alloy laser ultrasonic detection method based on GA-EE-VMD and a longitudinal wave enhancement algorithm, and the method specifically comprises the steps: 1, collecting a W-Cu alloy at a T temperature through employing a laser ultrasonic system, and obtaining an ultrasonic signal; 2, performing decomposition, reconstruction and de-noising processing on the acquired ultrasonic signals by adopting a GA-EE-VMD method to obtain K modal functions; 3, calculating instantaneous amplitudes and frequencies of different IMFs components, and carrying out weighted enhancement processing to obtain an enhanced longitudinal wave signal; and 4, the thickness of the W-Cu alloy at the high temperature is calculated through the enhanced longitudinal wave signals. According to the invention, the identification precision of the longitudinal wave is improved, so that the thickness detection precision is improved.

The invention belongs to the field of nondestructive testing, and relates to an all-optical non-contact ultrasonic nondestructive testing device, which utilizes a laser ultrasonic technology to excite a material to generate an ultrasonic signal, and is combined with a displacement table and a high-sensitivity optical microphone to realize detection and imaging of defects of a composite material plate. The whole system has the comprehensive advantages of no contact, no damage, high sensitivity, rapid signal response, strong environmental adaptability and the like, and can be widely applied to high-quality nondestructive detection requirements of various materials such as metal and nonmetal in the production, manufacturing, use and maintenance processes.

The invention discloses a metal fatigue damage detection method based on double-grating laser ultrasonic multi-parameter measurement, and relates to the technical field of metal fatigue damage detection. According to the invention, a double-cycle transient grating is formed on the surface of a to-be-detected metal material by using a pulse laser beam modulated by a double-spacing slit mask, so that double-frequency high-strength resonant ultrasonic surface wave non-contact excitation is realized, and an ultrasonic surface wave signal is acquired through a laser interferometer based on the non-contact excitation. And performing fast Fourier transform on the measurement signal to obtain frequency spectrum information of the measurement signal, and detecting the metal fatigue damage according to multiple laser ultrasonic characteristic parameters extracted from the frequency spectrum information. Ultrasonic detection on the surface of the metal material to be detected is achieved through an all-optical means, the effects of no damage, complete non-contact and high accessibility are achieved, and the detection precision and resolution of local fatigue damage are improved.

The invention relates to the technical field of nondestructive testing, in particular to a nondestructive testing method based on fusion of laser ultrasound and piezoelectric guided wave, which comprises the following steps: respectively carrying out preliminary detection by adopting a piezoelectric guided wave technology and a laser ultrasound technology; calculating the comprehensive credibility of the single-source model and inputting a multi-source model decision; constructing a basic probability distribution function based on a DS evidence theory to integrate detection results; and high-precision detection parameters are generated by using a weighted Dempster fusion algorithm. According to the method, the piezoelectric guided wave deep positioning capacity and the laser ultrasonic high-precision surface detection capacity are combined, the DS evidence theory and the weighted fusion algorithm are used for reducing the influence of environmental noise, the detection precision and efficiency are remarkably improved, and the method is suitable for defect detection of carbon fiber composite materials and other high-performance composite materials and has wide application prospects. And reliable technical support is provided for industrial application.

This invention discloses a machine learning-based method for predicting the properties of multilayer nanofilms. This method employs a machine learning neural network prediction model. Using an ultrafast laser ultrasonic experimental platform based on pump-probe technology and theoretical calculation methods, the method acquires instantaneous reflectivity change data. The dataset is then preprocessed and feature extracted. Finally, the obtained feature dataset is mapped to the film material properties. Using a network training algorithm, the method enables automated prediction of the material properties of multilayer nanofilm structures. This method is suitable for detecting the material parameters of multilayer nanofilms and can rapidly determine the internal structure, optical, and acoustic parameters of multilayer nanofilms with high detection accuracy.

A laser ultrasonic inspection apparatus includes a first laser light source, and a laser interferometer configured to use a second laser beam to detect a vibration of the target, wherein the laser interferometer includes a second laser light source configured to irradiate the target with the second laser beam, a light modulator configured use a vibrator to modulate a frequency of the second laser beam, a photodetector configured to receive the second laser beam from the light modulator and the second laser beam from the target to output a light reception signal, and a signal processor configured to detect the vibration based on the light reception signal and a reference signal, and measure, based on the reference signal, an elapsed time from the first laser light source emits the first laser beam to the vibration is detected, and the vibrator is a signal source of the reference signal.

This invention relates to the field of laser ultrasonic nondestructive testing technology, specifically a method for optimizing laser source parameters during laser-induced ultrasound based on FEA (Feature-Enhanced Amplification). The invention obtains the geometric dimensions and material parameters of the insulator under test, constructs a geometric model, adds solid heat transfer and mechanical fields, and establishes a finite element model through thermal expansion coupling. Multiple laser pulse width and laser spot radius values ​​are determined and combined to obtain multiple parameter schemes. Each parameter scheme is applied to the finite element model as the time and spatial distribution parameters of the laser heat source, and transient calculations are performed. Displacement time-domain data of monitoring points are extracted and subjected to Fast Fourier Transform (FFT) to obtain frequency-domain data. The ultrasonic signal characteristics of each parameter scheme are compared and analyzed, and the parameter combination that meets the testing requirements is selected as the optimization result. This invention significantly reduces parameter optimization costs and improves testing efficiency through simulation-guided experiments.

The invention provides a cross-domain transfer learning laser ultrasonic layering defect detection method suitable for a composite material and application thereof.The method comprises the steps that firstly, multi-channel input containing a frequency domain, a time-frequency domain and Koopman operator characteristics is constructed for the problem of data distribution deviation caused by the batch difference of the composite material; secondly, extracting and fusing high-dimensional spatial-temporal features through a multi-channel attention mechanism and a graph convolutional network; and finally, migrating the defect features of the source domain to the target domain in combination with dynamic distribution self-adaption and domain adversarial training strategies. The method can effectively overcome model performance reduction caused by material attribute change, realizes high-precision layering defect identification and imaging under the condition of no target domain label, and is suitable for composite material detection in a complex industrial scene.

The application discloses a kind of multi-thin-layer heterogeneous material elastic parameter in-situ nondestructive measurement method, medium and equipment, belong to ultrasonic measurement technical field.The method includes: for the structure to be measured, establish multi-mode ultrasonic propagation multi-parameter model, and calculate the propagation time theoretical value corresponding to each ultrasonic mode, the structure to be measured is multi-thin-layer heterogeneous structure;For the structure to be measured, laser ultrasonic linear scanning is carried out, and the ultrasonic signals of each ultrasonic mode propagating along different directions are collected to obtain linear scanning ultrasonic data set;For selected ultrasonic mode, the propagation time experimental value under different excitation-receiving point combinations is extracted in the ultrasonic signal of the linear scanning ultrasonic data set;For the selected ultrasonic mode, the difference between the propagation time theoretical value and the propagation time experimental value is used as the objective function to minimize, and the elastic parameters of the structure to be measured are inverted using parameter optimization algorithm.The application can realize long-distance, non-contact in-situ nondestructive measurement, and simple operation.

The invention relates to the technical field of high-voltage insulator detection, and provides a high-voltage insulator transverse crack laser ultrasonic non-contact detection method which comprises the following steps: step 1, building a detection system which comprises an industrial personal computer, a pulse laser, a light path system, an ultrasonic receiving system and a scanning system, the pulse laser and the ultrasonic receiving system are in two-way communication with the industrial personal computer through optical fibers, the optical path system is fixed to the scanning system, and the scanning system receives control signals of the industrial personal computer through an industrial bus. And 2, outputting a synchronous trigger signal by the industrial personal computer, and controlling the pulse laser to emit nanosecond laser with the wavelength of 1064nm. Live detection is realized through a non-contact design, and a blind area of a compact insulator is eliminated; the efficiency is improved by means of collaborative scanning, and batch standardized detection is met; the multi-modal fusion and standardization algorithm improves the recognition precision and realizes quantitative detection, the method can also adapt to the outdoor environment to reduce the misjudgment rate, and an efficient, accurate and reliable detection scheme is provided for power grid operation and maintenance.

The application belongs to the technical field of ultrasonic detection, and discloses a subsurface defect detection method, device, equipment and storage medium. The method comprises the following steps: acquiring surface roughness and surface material corresponding to a metal sample to be detected; searching for corresponding optimal laser detection power from a database according to the surface roughness and the surface material; and performing laser ultrasonic detection on the metal sample to be detected based on the optimal laser detection power, so as to obtain a subsurface defect detection result corresponding to the metal sample to be detected. In the above manner, the optimal laser detection power is selected according to the roughness and material of the metal sample for laser ultrasonic detection, so that the laser ultrasonic detection precision and efficiency are effectively improved, and the accuracy of metal subsurface defect detection is further improved.

The application relates to a laser ultrasonic microscopic imaging system, method and device, wherein the laser ultrasonic microscopic imaging system comprises an excitation light source for emitting excitation light, a detection light source for emitting detection light, a first modulation module for modulating the deflection angle of the excitation light and reflecting the excitation light, a second modulation module for modulating the deflection angle of the detection light and reflecting the detection light, and an optical path converter, wherein the excitation light and the detection light form laser spots and detection spots on a sample surface, and a detection module and a data processing module are used to receive and process the detection light reflected from the sample surface to obtain an ultrasonic wave velocity image of the sample surface. The first modulation module and the second modulation module are used to high-speed modulate the excitation light and the detection light, so that the effect of rapidly measuring and imaging the ultrasonic wave velocity of the sample surface is achieved.

The application provides a wheel hub detection method and system, which comprises the following steps: placing a wheel hub on a preset detection platform through a preset mechanical arm, and driving the wheel hub to rotate at a constant speed through the preset detection platform; during the rotation of the wheel hub, a to-be-detected area matched with the wheel hub is calibrated in real time, and the to-be-detected area is scanned in full through a preset laser ultrasonic detector; ultrasonic signals generated by the preset laser ultrasonic detector during the scanning are collected in real time, and a cross-sectional image corresponding to the wheel hub is simulated synchronously; the ultrasonic signals and the cross-sectional image are synchronously input into a preset CNN model, and whether the wheel hub has defects is judged in real time through the preset CNN model. The application can objectively and accurately judge whether the wheel hub has defects, and the detection efficiency is improved correspondingly.

The invention discloses a laser ultrasonic detection system and a laser processing quality detection method, and belongs to the technical field of laser processing quality detection.The laser ultrasonic detection system comprises a first laser transmitter, a spectroscope, a scanning lens, a second laser transmitter, a detection lens, a laser ultrasonic receiver, a third laser transmitter and a mobile platform; the first laser emitter emits a first laser beam, the first laser beam passes through the spectroscope and the scanning lens and then irradiates a workpiece, the second laser emitter emits a second laser beam, and the second laser beam passes through the detection lens and irradiates the workpiece. Reflected light beams, irradiated to the workpiece, of the second laser beam and the third laser beam are received by the laser ultrasonic receiver, defect detection is conducted on the workpiece in a non-contact detection mode, online detection can be achieved, ultrasonic signals are transmitted through laser, and the anti-interference capacity is high.

The invention provides a surface crack laser ultrasonic quantitative detection method, device, equipment and medium, and relates to the technical field of nondestructive detection.The method comprises the steps that laser ultrasonic B-scanning data are obtained through synchronous scanning, a multi-modal characteristic wave propagation mechanism is analyzed, a flight time analysis model is established, and the flight time analysis model is analyzed; and a theoretical and experimental multi-modal characteristic mode is constructed, and discretization similarity matching is carried out, so that the depth and the inclination angle of the surface crack are stably inverted in a full-parameter space, and quantitative detection is realized. According to the method, instability caused by dependence of a single mode or a single characteristic can be avoided, synchronous and high-precision quantitative detection on the surface crack depth and the crack inclination angle under the condition of complex multi-mode wave aliasing is realized, and the problems of insufficient characterization accuracy and robustness of geometric parameters of cracks in the prior art are solved.

The utility model discloses a laser ultrasonic nondestructive detector for metal welding residual stress, which relates to the technical field of residual stress detection equipment and comprises a box body, a mounting groove is formed in the box body, and a plurality of first rotating shafts are rotatably connected in the mounting groove. The spring winding device has the advantages that the rotating roller and the first rotating shaft are driven to rotate when the two ends of a connecting wire are pulled, so that a spring is wound, meanwhile, through mutual cooperation of the first rotating shaft, a ratchet wheel, a second rotating shaft and a pawl, the connecting wire is wound, and the connecting wire is wound. After use, a push plate is pushed to slide towards the interior of a push groove, then a push rod and a second connecting plate are pushed, and then a first connecting plate and a second rotating shaft are driven to rotate, so that a pawl is driven to rotate, limiting of the pawl to a ratchet wheel is relieved, and the spring rebounds; and therefore, the first rotating shaft and the rotating roller can be driven to wind the connecting wire.

The invention discloses a laminated iron core bonding manufacturing method, which belongs to the field of motors, and comprises the following steps: performing laser texturing on the surface of a plate made of amorphous alloy, and etching a microstructure on the surface of the plate; dispensing and laminating the plurality of plates to form a plurality of layers of plates; blanking the multi-layer plate to form a plurality of multi-layer laminated sheets; a plurality of multi-layer laminations are stacked in the height direction, glue dispensing is conducted on the surface of each multi-layer lamination in the stacking process, the multiple stacked multi-layer laminations are laminated and cured, laser ultrasonic scanning is conducted on the manufactured iron core, the iron core generates reflected waves and transmitted waves, the reflected waves and the transmitted waves are collected, and the iron core is obtained. According to the method, damage reflected waves are extracted from aliasing signals, abnormal waves are captured, energy space-time distribution characteristics of a damage sensitive frequency band are extracted, imaging is carried out, plane positioning, size inversion and morphology reconstruction of debonding defects are achieved, a laminated iron core is made of an amorphous alloy material, and the amorphous alloy material is not damaged due to the fact that a bonding method is adopted for manufacturing.

The application provides a gradient material thickness measurement method and system based on laser ultrasonic dispersion spectrum, and relates to the technical field of laser measurement, and comprises the following steps: modulating excitation laser through an optical mask to form a transient grating with periodic intensity distribution, exciting ultrasonic waves with specific frequencies in a material to be measured by using the transient grating, and receiving Lamb wave signals generated by the structure of the material to be measured by using a laser interferometer for line scanning; performing two-dimensional Fourier transform on the Lamb wave signals to obtain a target dispersion curve; the target dispersion curve comprises a mapping relationship between signal frequencies and wave numbers; a sample pair composed of multiple groups of material thickness parameters and dispersion curve parameters is generated by using a transfer matrix algorithm, and a preset deep neural network is trained based on the sample pair until a loss function reaches a preset threshold range, so that a target neural network is obtained; and the target dispersion curve is input into the target neural network to obtain thickness parameters of the material to be measured.