457 results about "Ultrasonic guided wave" patented technology

The present application provides a method for pipeline defect detection using the magnetostrictive characteristics of ultrasonic guided waves, which relates to the technical field of pipeline defect detection, including: obtaining the geometric and material parameters of multi-layer heterogeneous pipelines, and establishing a mathematical model of the pipeline; according to the mathematical model, calculating the dispersion curve and modal characteristics of ultrasonic guided waves in the pipeline; selecting a suitable excitation frequency and guided wave mode, and optimizing the detection parameters of ultrasonic guided waves; presetting defects of different types and sizes in the pipeline, and analyzing the influence of defects on guided wave propagation characteristics through numerical simulation; building a multi-layer heterogeneous pipeline ultrasonic guided wave detection experimental system, collecting guided wave signals under different defect conditions, and extracting time-frequency domain characteristic parameters. The present invention can realize the effective detection and evaluation of internal defects of multi-layer heterogeneous pipelines at different temperatures, and provides an important technical means for ensuring the safe operation of pipelines.

The invention provides an engine internal damage identification method and system based on target detection, and the method comprises the steps: obtaining the distribution of thermal stress and mechanical stress under different working conditions through finite element analysis for typical working conditions of high temperature, high pressure and heat engine coupling load according to the structural characteristics and fault modes of an engine cylinder; processing an ultrasonic guided wave signal through a synthetic aperture focusing algorithm, reconstructing a three-dimensional shape of a crack by combining a three-dimensional geometric model of the cylinder body and guided wave propagation characteristics, and determining a crack propagation rate so as to analyze crack propagation of the cylinder body; the residual service life of the cylinder body under the given working condition is predicted according to the crack size, the crack growth rate and the high-risk working condition parameters in combination with the material mechanical property parameters of the fracture toughness; and according to the crack instability critical length, the cylinder body crack propagation analysis result and the high-risk working condition judgment result, the engine operation working condition is optimized, the occurrence frequency of the high-risk working condition is reduced, the service life of the cylinder body is prolonged, and the crack detection and recognition precision is improved.

The invention provides a high-temperature chemical pipeline defect detection system and method based on magnetostrictive ultrasonic guided waves, and relates to the technical field of high-temperature chemical pipeline defect detection.The method comprises the steps that magnetostrictive excitation signals are applied, the propagation process of the guided waves in a pipeline is calculated through numerical simulation, and the amplitude and phase information of guided wave signals is obtained; performing time-frequency domain analysis on the guided wave signal, extracting group velocities and phase velocities of guided waves in different modes, determining frequency dispersion characteristics of the guided waves, and evaluating the influence of a high-temperature environment on guided wave propagation; processing the received guided wave signal by adopting a modal decomposition and reconstruction algorithm to obtain a corrected guided wave signal; and carrying out feature extraction and parameter estimation on the corrected guided wave signal to obtain the position, size and type information of the pipeline defect. According to the invention, the problem of multilayer heterogeneous pipeline guided wave detection in a high-temperature environment is solved, the accuracy and reliability of defect detection are improved, and an effective method is provided for pipeline health monitoring and safety assessment.

The invention provides a crane balance beam crack defect detection method and system, and relates to the technical field of defect detection.The crane balance beam crack defect detection method comprises the steps that a plurality of ultrasonic guided wave sensor arrays are arranged on the surface of a crane balance beam to be detected, ultrasonic guided wave signals in the balance beam are collected, and ultrasonic guided wave time-frequency domain feature vectors of the balance beam are constructed; constructing a three-dimensional finite element simulation model of the crane balance beam to obtain multiple groups of balance beam crack defect expansion strain field data, and constructing a crack defect deformation ultrasonic-strain field fusion feature vector; training a crack defect deformation detection intelligent discrimination model by using the crack defect deformation ultrasonic-strain field fusion feature vector, obtaining a time-frequency domain feature vector and a strain distribution feature vector of the crane balance beam to be detected, and inputting the time-frequency domain feature vector and the strain distribution feature vector into the trained crack defect deformation detection intelligent discrimination model for intelligent discrimination screening. And outputting a crack defect detection result of the balance beam to be detected, wherein the crack defect detection result comprises the type, size, form and specific position of the crack defect.

The invention provides a shield tunnel longitudinal seam joint recessive damage diagnosis method based on multi-mode ultrasonic guided waves, and the method comprises the steps: applying orthogonal polarization in a specific region of a longitudinal seam joint, and forming a space-time coupled guided wave interference pattern in the whole region of the longitudinal seam joint; the acquired guided wave interference map is utilized to separate baseline interference characteristics and abnormal disturbance components caused by hidden damage through multi-physics field reverse decoupling, and the abnormal disturbance components are represented as energy abnormal attenuation and phase distortion in a specific polarization direction; constructing a three-dimensional damage sensitive vector field in the longitudinal seam joint; and carrying out dynamic manifold topology analysis by utilizing the generated three-dimensional damage sensitive vector field, identifying topological characteristics in the three-dimensional damage sensitive vector field, and tracking a migration path and an intensity evolution trajectory of the topological characteristics along with the change of the detection condition. According to the method, full-dimension diagnosis and evolution prediction of the hidden damage of the longitudinal joint connector of the shield tunnel are realized.

The invention provides a body armor composite interlayer defect positioning method and system based on multi-modal nondestructive testing, electronic equipment and a storage medium, and relates to the technical field of nondestructive testing. Ultrasonic guided wave, pulsed eddy current and infrared thermal wave excitation signals are synchronously applied to a body armor composite interlayer, and multi-modal response signals of all positions are collected; and generating an original multi-modal response signal set. And inputting the signal into a pre-trained deep convolutional neural network, determining a target frequency band parameter and a target noise suppression parameter of each modal response signal, and outputting an adaptive modulation parameter group. Performing frequency domain filtering and noise suppression processing on an original signal set to generate an optimized signal set, inputting spatial frequency features into a cross-modal feature fusion model, adaptively associating defect sensitive features of different modals through an attention mechanism in the model, and generating a three-dimensional defect distribution diagram of the composite interlayer, thereby realizing millimeter-level precision defect positioning. The precision and efficiency of body armor composite interlayer defect positioning can be improved.

The invention relates to a metal sheet detection method, system and device, computer equipment and a storage medium. The method comprises the following steps: controlling an ultrasonic guided-wave probe to generate an ultrasonic guided-wave signal under the condition that a metal sheet is transmitted to a preset detection area, so that the ultrasonic guided-wave signal is propagated in the metal sheet; acquiring a reflection echo signal of the metal sheet; performing feature analysis on the reflection echo signal to obtain a feature analysis result; and detecting whether the metal sheet has defects or not according to a feature analysis result to obtain a defect detection result of the metal sheet. The method is beneficial to improving the detection efficiency of the metal sheet.

The invention relates to a multi-defect ultrasonic guided wave nondestructive testing, positioning and recognition method based on a mechanical arm, relates to the technical field of nondestructive testing and automatic testing, and solves the technical problems that in the prior art, time and labor are consumed in detection of large components, and positioning recognition and detection precision is difficult to guarantee in a manual detection mode. The method comprises the following steps of: post-processing signals acquired for N times, and setting a signal amplitude threshold value; performing global scanning on the tested piece; and whether the mechanical arm completes global scanning or not is judged. A mechanical arm is used for carrying an electromagnetic acoustic sensor to scan a large plate and a large curved surface structure, and detection and positioning recognition of various different defects are achieved; using the collected data as an original data set to construct a deep learning model and an integrated CNN model, and realizing adaptive scanning detection of internal defects of a large component and a large curved surface structure; the use of a coupling agent is reduced, the detection time efficiency and the detection precision are improved, and the detection accuracy and the defect positioning accuracy are realized.

The invention discloses a steel-concrete joint surface defect identification method based on air coupling ultrasonic guided waves, which comprises the following steps: S1, selecting an ultrasonic guided wave mode and a probe frequency, and determining an incident angle theta of an air coupling excitation probe; s2, constructing a detection system according to the parameters in the step S1; s3, constructing a data set, wherein the acquisition mode of the sample of the ultrasonic guided wave signal in the data set comprises the following steps of: performing actual detection by adopting the detection system to obtain the sample of the ultrasonic guided wave signal; by solving the air coupling ultrasonic three-dimensional finite element calculation model, obtaining a sample of an ultrasonic guided wave signal under the condition that interference factors and joint surface defects exist; s4, training the recognition model by using the data set; the input of the recognition model is the time domain feature and the frequency domain feature of the ultrasonic guided wave signal, and the output of the recognition model is a defect probability value of a measuring point corresponding to the ultrasonic guided wave signal; and S5, identifying the ultrasonic guided wave signal of each measuring point by adopting the trained identification model so as to calculate the defect probability of each measuring point.

The invention discloses an ultrasonic guided wave signal noise reduction method based on HHO-SVMD and singular spectrum analysis, and the method comprises the steps: obtaining a to-be-processed ultrasonic guided wave signal, optimizing a penalty factor of variation mode decomposition (SVMD) through employing an improved Harris eagle algorithm, initializing a population through Circle chaotic mapping, introducing chaotic disturbance and weight, and carrying out the noise reduction of the to-be-processed ultrasonic guided wave signal. Determining an optimal alpha value and decomposing the signal into an optimal modal component; calculating a kurtosis value of each modal component, and screening effective components containing damage information according to a threshold value; singular spectrum analysis denoising is carried out on the effective components, and a self-adaptive window mechanism is introduced to dynamically adjust the window length and the truncation strength; reconstructing the de-noised effective component to obtain a de-noised signal; according to the method, the parameter optimization precision and efficiency are improved, damage characteristics and noise are effectively separated, different dominant frequency signals are adapted, the damage characteristics can still be reserved in a low-signal-to-noise-ratio environment, the noise reduction effect of ultrasonic guided wave signals and the damage detection reliability are improved, and the method is suitable for nondestructive detection of components such as ultra-long small-diameter heat absorption pipes.

The invention discloses a newly-built structure prestress and duct defect integrated monitoring device and method.The device comprises integrated monitoring sensors pre-buried in a concrete structure, and the integrated monitoring sensors wrap the periphery of a prestressed tendon in a sleeve mode and are arranged in an array mode in the length direction of the prestressed tendon; the functions of an electromagnetic elastic absolute stress sensor and a magnetostrictive ultrasonic guided wave transducer can be realized at the same time; an outer-layer coil in the sensor can serve as a magnet exciting coil of an electromagnetic elastic absolute stress sensor and a bias magnetizing coil of a magnetostrictive ultrasonic guided wave transducer at the same time, a magnetoelectric conversion element is used for collecting magnetic characteristic signals of a to-be-tested prestressed tendon, and an inner-layer coil is used for exciting and receiving ultrasonic guided waves. Reflection and transmission signals between different sensors can be compared, and damage positioning and quantification are achieved. The device can simultaneously measure information such as various damages and stresses in the component, and has the characteristics of convenience in operation, long-term monitoring, high monitoring precision and the like.

The invention relates to the technical field of wind power equipment detection, in particular to a wind turbine generator blade fracture damage detection method applying an inspection robot, which comprises the following steps of: S1, constructing a blade three-dimensional point cloud model and positioning the position of the robot in real time through a laser radar and a visual SLAM (Simultaneous Localization and Mapping) module carried on a robot body; s2, generating a spiral detection path covering the surface of the blade based on a path planning algorithm optimized by the genetic algorithm; s3, synchronously collecting blade surface data by adopting a multi-mode sensor array, wherein the blade surface data comprise pulse thermal imaging data, ultrasonic guided wave signals and high-resolution visible light images; s4, performing feature fusion on the acquired data through a deep convolutional neural network; through multi-modal sensor cooperative detection, deep learning feature fusion and digital twinborn evaluation technologies, full-process automatic detection from damage identification to life prediction is realized, the detection precision and efficiency are significantly improved, and reliable guarantee is provided for safe operation of the wind turbine generator.

The invention relates to a mechanical arm ultrasonic guided wave multi-defect detection path planning method based on data driving, relates to the technical field of nondestructive detection and automatic detection, and solves the technical problem that automatic defect detection for a large plate structure and a large curved surface structure does not exist in the prior art. A system applicable to the method comprises a control and test system and a tested piece. According to the invention, the mechanical arm is used for carrying the electromagnetic acoustic sensor to scan a large plate and a large curved surface structure, so that detection, positioning and identification of various different defects are realized; the use of a coupling agent can be reduced, the detection time efficiency is improved, the detection precision is improved, the detection accuracy is realized, and the accuracy of positioning and identifying defects is improved; the scanning path of the mechanical arm is optimally designed, so that the detection efficiency is improved; and the collected data serve as an original data set to construct a deep learning model and an integrated CNN model, and mechanical arm scanning detection path planning of multiple defects in a large component and a large curved surface structure is achieved.

The invention discloses a nonlinear ultrasonic guided wave detection system based on multi-channel receiving, and the system comprises a high-energy fundamental frequency ultrasonic excitation module which is controlled by a trigger signal to generate an electric signal and carries out the amplification and filtering processing; the transmitting transducer generates ultrasonic waves to act on a target object under the excitation of the high-energy fundamental frequency ultrasonic excitation module; the variable-angle receiving transducer array is used for receiving the ultrasonic guided wave signal fed back by the target object and converting the ultrasonic guided wave signal into a feedback electric signal; the ultrasonic acquisition module is used for amplifying the feedback electric signal, sampling the feedback electric signal and converting the feedback electric signal into a digital signal under the instruction of the control and signal processing module; the control and signal processing module comprises an FPGA (Field Programmable Gate Array) chip and an ARM (Advanced RISC Machines) main processor, and is used for controlling the generation of an instruction and performing time domain-frequency domain-space domain information extraction on the digital signal sent by the ultrasonic acquisition module, and calculating to obtain a material nonlinear parameter carried by the guided wave signal; and performing micro-damage evaluation and life prediction based on the nonlinear parameters of the material.

The invention relates to an ultrasonic guided wave array detection method and system for orthotropic steel bridge deck cracks, and the method comprises the steps: employing an ultrasonic guided wave generator to apply ultrasonic guided waves propagating in a second direction to a plurality of set areas delimited in a first direction on a steel bridge deck one by one, a signal receiver is adopted to receive a reflection signal of the ultrasonic guided wave; a preset signal analysis model is adopted to carry out intelligent processing on the reflection signals, the intelligent processing comprises signal data preprocessing, first module strength feature analysis based on a dense block convolutional neural network and second module time sequence dependency analysis based on a bidirectional long-short-term memory neural network, and therefore cracks are accurately recognized; in addition, the invention further provides a detection system for executing the method. The crack detection method provided by the invention is simple and convenient to operate, solves the problem that a traditional detection method is difficult to fully cover, and improves the accuracy and efficiency of detection.

The invention provides an ultrasonic detection method and system for inverting residual stress by using sound wave phase velocity, and belongs to the field of air coupling ultrasonic guided wave detection. The method is based on an air coupling ultrasonic guided wave sound field propagation finite element model, and guides optimization design of air coupling ultrasonic transducer parameters. The air coupling ultrasonic guided wave detection technology is adopted for conducting non-contact excitation and receiving of guided wave signals on the composite material component with the preset stress through the stretcher. And calculating the phase velocity of the air-coupled ultrasonic guided wave in the composite material component based on a geometric positioning and time difference cooperative gradual difference method. And calibrating the phase velocity in the target composite material and preset stress to obtain a corresponding relational expression, performing phase velocity detection on a composite material component with unknown stress based on a calibration result of the target composite material, and performing inversion to obtain composite material construction residual stress. By adopting the method and the system, the residual stress detection of the composite material component is realized.

The invention relates to a pipeline ultrasonic guided wave detection system which comprises a plurality of detection units distributed in the circumferential direction of a pipeline, a tightening assembly is hinged between the head detection unit and the tail detection unit, a connecting assembly is hinged between the other adjacent detection units, each detection unit comprises a frame and a probe detachably fixed in the frame, and two supports are arranged on the two sides of the frame respectively. A guide rod is arranged in the support, a roller is mounted on the guide rod through a wheel carrier, a first spring is arranged between the wheel carrier and the support, the probe comprises a shell, and a bottom-layer insulating spacer, an annular permanent magnet, an upper-layer insulating spacer and a disc-shaped electromagnetic coil which are fixed in the shell, a rectangular hole is formed in the bottom wall of the shell, and strip-shaped stop blocks are arranged on the two sides of the rectangular hole respectively; the bottom insulation spacer is connected with a coupling patch through a flexible deformable body, the disc-shaped electromagnetic coil is connected with an industrial interface extending out of the shell, the flexible deformable body is made of silica gel, and the coupling patch is made of ferrocobalt. The device has the advantages of being simple in structure, convenient to operate and control, high in reliability and good in adaptability.

The invention discloses an ultrasonic guided wave signal and key feature extraction method, system and device based on deep learning and a medium, and belongs to the technical field of ultrasonic guided wave signal and key feature extraction, and the method comprises the steps: collecting a guided wave signal of a steel strand, and carrying out the preprocessing of the guided wave signal; converting the pre-processed guided wave signal into a time-frequency spectrum, extracting a frequency peak value, envelope energy and group velocity features, and performing dimension reduction processing on a feature set to generate a feature vector; inputting the feature vectors into a deep learning network model, extracting convolution features and time sequence features of the signals, and completing model parameter updating based on a training sample; the trained deep learning network model is used for reasoning the steel strand guided wave signals, classification labels of corrosion types and regression prediction values of corrosion depths are output, and the specific positions and corrosion degrees of defects are judged. According to the method, the positioning precision, the recognition accuracy and the cross-scene robustness of the ultrasonic guided waves on the corrosion defect of the steel strand under the complex working condition are remarkably improved.

A movable ultrasonic reflection clamping member for a pipe and an ultrasonic guided wave testing calibration method. The movable ultrasonic reflection clamping member (5) is openable and closable, can be mounted on the outer wall of a pipe and is used for reflecting ultrasonic guided waves. A main body of the movable ultrasonic reflection clamping member (5) consists of two semicircular components (1) of which inner walls are covered with ultrasonic coupling agent coatings (2), a constraint connecting member (3) and an opening and closing connecting member (4). The ultrasonic guided wave testing calibration method comprises: performing guided wave testing on a calibration pipe (6) provided with a movable ultrasonic reflection clamping member (5), so as to acquire a set of data comprising the echo amplitude and the mounting point (7) position of the reflection clamping member, and finally calculating data, such as a DAC, which represents the ultrasonic guided wave echo attenuation of the pipe.

The invention discloses an aviation composite material-oriented ultrasonic guided wave damage rapid imaging method, which relates to the field of nondestructive testing, and comprises the following steps: calculating a frequency dispersion curve according to material parameters of a carbon fiber composite material plate, and obtaining an ultrasonic optimal excitation angle and an ultrasonic guided wave propagation mode; scanning and collecting two groups of ultrasonic guided wave signals in the orthogonal direction in sequence; decomposing the guided wave signal, and obtaining a reconstructed ultrasonic guided wave signal after extracting a target component according to the size of an energy entropy value; calculating time-frequency information and energy of the signal, and estimating the damage probability in the scanning path by combining a damage index; embedding the expansion kernel convolution and the double probability distribution function into the damage index curve to respectively realize the reinforcement of the damage index and the sharpening of the edge; and expanding the two groups of damage index curves in the orthogonal direction into a two-dimensional damage matrix, and imaging according to a composite path cross imaging method, thereby finally realizing damage positioning imaging of the carbon fiber composite material plate.

The invention belongs to the field of ultrasonic guided wave detection, and relates to an ultrasonic guided wave damage positioning method of a gated differential attention unit network, which comprises the following steps: acquiring and preprocessing an ultrasonic guided wave scattering signal xS to obtain an energy density signal xE, and inputting the signals xS and xE into a trained damage positioning model to obtain a damage position; the training process of the damage positioning model comprises the following steps: inputting an ultrasonic guided wave scattering signal xS into a scattering wave feature extraction module to obtain a scattering wave feature fS; inputting the energy density signal xE into an energy density feature extraction module to obtain an energy density feature fE; inputting the features fS and fE into a feature fusion module to obtain a fusion feature; inputting the fused features into a prediction module to obtain a predicted damage position; updating parameters of the damage positioning model according to the predicted damage position until a trained damage positioning model is obtained; the gating differential vector attention unit excavates difference information between two adjacent moments so as to guide updating of a network state, and the model damage positioning capability is improved.

The invention relates to the technical field of detection, particularly discloses an ultrasonic guided wave non-contact accurate liquid level measurement method for a high-temperature closed container, and aims at solving the problems that in the prior art, measurement precision is low and interference is prone to occurring in a high-temperature environment. Effective signals are extracted through a self-adaptive interference suppression algorithm, the liquid level is calculated through multi-source data fusion, and an intelligent calibration and self-diagnosis system and a machine learning prediction model are arranged. Experiments show that the measurement error of the method can be controlled within + / -3cm, and the method is remarkably superior to a traditional method and is suitable for accurate liquid level measurement of high-temperature closed containers in the industries of chemical engineering, electric power and the like.

The invention relates to the technical field of computer simulation testing, in particular to a dynamic analogue simulation testing method and system for plate type structure service deformation. The technical problem that the structural damage identification precision is insufficient when fixed signal decomposition parameters are used for processing all detection signals is solved. The method comprises the following steps: acquiring a mesoscopic parameter set and a bimodal ultrasonic guided wave original signal set of a to-be-detected plate type structure; based on the mesoscopic parameter set, determining optimization parameters for decomposing the bimodal ultrasonic guided wave original signal set; decomposing the bimodal ultrasonic guided wave original signal set based on the optimized parameters and a signal decomposition algorithm, and determining a target signal set related to structural damage; and performing simulation comparison on the mesoscopic parameter set and the target signal set, and determining the service damage state of the plate type structure. The method is used for plate type structure damage identification scenes.

The present invention relates to the field of nondestructive testing technology and provides a composite material damage imaging method based on the spatiotemporal cross-correlation of ultrasonic guided wave wavefields. The method comprises the following steps: S1, acquiring a wavefield signal of the plate being tested; S2, performing narrowband signal extraction on the wavefield signal; S3, filtering the wavefield signal after narrowband signal extraction; S4, shifting the wavefield signal to obtain wavefield signal cross-correlation features; and S5, using a convex hull algorithm to obtain damage imaging results. This method innovatively extracts the difference coefficient between wavefield signals as a basis for damage location, providing a new approach to feature extraction algorithms based on the time-frequency domain. This method enables automated identification of composite material delamination damage and is sensitive to both surface and internal damage.

The invention relates to a novel ultrasonic descaling device and pipeline combination structure, and provides a novel ultrasonic transducer array design and a pipeline combination mode. Four ultrasonic transducers and a trapezoidal module with an inclined angle are combined, and the trapezoidal module and the pipeline are combined in a curvature mode. The trapezoidal module and the ultrasonic transducer are linked through spiral occlusion, so that the problems that the ultrasonic transducer is lost due to welding combination of the ultrasonic transducer and the pipeline, the ultrasonic transducer falls off after working and the like can be avoided, and later maintenance and replacement are facilitated. The trapezoidal module can provide a certain inclination angle, so that ultrasonic body waves emitted by the ultrasonic transducer are converted into ultrasonic guided waves, and the pipeline cleaning length of the ultrasonic descaling device is increased.

The invention discloses an intelligent pipe network leakage active prediction and early warning system based on multi-technology fusion, and the system comprises a multi-source heterogeneous data fusion collection module, a spatial-temporal feature depth extraction module, a degradation trend prediction and residual life evaluation module, and a multi-stage early warning and decision generation module. The multi-source heterogeneous data fusion acquisition module acquires and fuses ultrasonic guided wave signals, pressure flow time sequence data and environmental factor data; the spatial-temporal feature depth extraction module extracts spatial-temporal fusion features through continuous wavelet transform and a CNN-LSTM hybrid network; the degradation trend prediction and residual life evaluation module determines a degradation level, predicts residual life and quantifies a pipe explosion risk probability; the multi-stage early warning and decision generation module generates graded early warning signals and maintenance strategy suggestions, the technology crossing from post-event detection to pre-event prediction is realized, and the scientificity and refinement level of operation and maintenance management of a pipe network are effectively improved.

The invention provides a high-sensitivity and anti-counterfeiting ultrasonic guided wave fingerprint imaging and authentication method, which comprises the following steps of: constructing an ultrasonic transducer for fingerprint acquisition, placing the ultrasonic transducer on an optical sensor, and acquiring a sound field signal and a fingerprint grayscale image of a fingerprint; preprocessing the fingerprint grayscale image, and establishing a fingerprint speed model; extracting a first-motion wave time domain signal segment in the sound field signal of the fingerprint, and establishing a frequency domain sound field matrix; establishing an offline training data set of fingerprint imaging, and obtaining a descent gradient matrix through offline training; a post-processing model for image inpainting and detail matching is built and trained; performing online inversion through the descent gradient matrix to obtain a fingerprint inversion image of the test case; inputting the fingerprint inversion image into the trained post-processing model to obtain a fingerprint matching result; and calculating personal authentication confidence by using a fingerprint matching result, and identifying the fingerprint to be authenticated. According to the invention, the form of the fingertip epithelium can be effectively discriminated from the sound field response even under the condition of environmental pollution, and the method has the characteristics of zero occupation of the space under the ultrasonic transducer screen, high-sensitivity imaging, authentication and anti-counterfeiting.

The invention discloses a method for measuring the thickness of an oil film on the surface of a bearing bush and pressure distribution based on ultrasonic guided waves. The method comprises the following specific steps: step 1, embedding a piezoelectric plate array in the back of a to-be-measured bearing bush; step 2, acquiring a reference signal, changing oil film pressure and film thickness, and acquiring a guided wave signal; step 3, acquiring a noise signal, and performing trend noise fitting on the noise signal; 4, after trend noise fitting is completed, a segmented RMS index is established, and pressure and film thickness features are extracted; and 5, importing the extracted guided wave data into a convolutional neural network in deep learning to decouple coupling features, and imaging the surface of the bearing bush by using an RAPID imaging algorithm based on a probability damage imaging principle to complete measurement. According to the bearing bush surface oil film thickness and pressure distribution measuring method based on the ultrasonic guided waves, the thickness of the oil film can be accurately calculated, and the pressure of the oil film can be calculated.

The present invention discloses a method and a system for enhancing an ultrasonic guided wave signal based on multi-modal recognition and fusion. The method includes: solving an ultrasonic guided wave frequency dispersion curve of a detected structure, selecting target detection modes, and setting the strongest energy mode as the main mode; forming a frequency dispersion dictionary and obtaining sub-signals, then converting their abscissa axes from time to signal source distances; grouping sub-signals with similar source distances, classifying them as single modal or main mode conversion sub-signals, and removing interference signals; and resampling the classified sub-signals at a uniform frequency, extracting half-wave envelope signals, and superposing them within each source group to obtain an enhanced target signal

The invention discloses an ultrasonic guided wave damage identification method based on twin data driving, and the method comprises the steps: collecting an aluminum sheath damage detection twin model ultrasonic guided wave signal as a source domain data set 1 in a laboratory, extracting and constructing a source domain data set 2 through an ultrasonic guided wave signal mode, and constructing a target domain data set through a real detection signal; preprocessing a source domain data set and a target domain data set by adopting continuous wavelet transform according to the established data set; common feature extraction of the source domain data set and the target domain data set is realized through a ResNet50 network; a specific domain feature extractor is constructed, and two strategies of intra-domain alignment and inter-domain alignment are adopted to align data in different distributions so as to obtain domain invariant features and eliminate offset; and finally, designing a specific domain classifier to obtain category separable features, eliminating differences among different classifiers, and performing verification in damage detection of the cable sheath. According to the method, the interpretability, universality and generalization ability of the damage detection model are enhanced.