137 results about "Ultrasonic guided wave" patented technology

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 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 relates to the technical field of signal processing, in particular to a pipeline guided wave signal processing method and system. The method comprises the following steps: acquiring a multi-channel ultrasonic guided wave signal through a sensor array circumferentially arranged around a pipeline, and converting the multi-channel ultrasonic guided wave signal into a frequency domain response matrix; calculating a circumferential amplitude distortion degree based on the power spectrum amplitude distribution of each channel; constructing a modal coupling matrix by combining the circumferential amplitude distortion degree and the theoretical wave number of the ideal pipeline; correcting the standard orthogonal modal matrix to generate a modal projection matrix; and decomposing the frequency domain response matrix by using the projection matrix, and separating a structure echo component and a defect signal component. According to the method, the influence of geometric defects such as ovality deviation is evaluated more accurately, energy exchange between modeling modes is accurately established, and orthogonality hypothesis is corrected; modal energy leakage is inhibited, and the decomposition accuracy is improved; signals are effectively separated, coherent noise interference is solved, and the accuracy and reliability of pipeline defect detection are improved.

The invention discloses a bone injury detection method based on ultrasonic guided waves and a multi-branch convolutional neural network, and the method comprises the steps: firstly collecting UGW signals of bone tissues, and carrying out the standardization preprocessing of the UGW signals, so as to eliminate the amplitude difference between different samples; then, data enhancement strategies such as Gaussian noise disturbance and amplitude scaling are adopted, a finite sample set is effectively expanded, and the robustness and generalization ability of the model are improved; a multi-branch convolutional neural network (TB-CNN) structure is constructed, the network designs independent branches for time domain, frequency domain and time-frequency domain input, deep features are automatically extracted from the respective branches, and feature splicing and multi-level information integration are realized in a fusion module; finally, regression prediction of the bone injury depth is realized through a full connection layer, so that continuous value output is obtained, and the severity of the bone injury can be reflected more finely.

The invention relates to the technical field of ultrasonic detection, in particular to a cable aluminum sheath defect grading detection method based on multi-frequency guided waves, which comprises the following steps: determining propagation characteristics of each guided wave mode according to a frequency dispersion curve, and determining excitation frequency for detecting a main mode based on the propagation characteristics; arranging and installing a transducer array on the cable aluminum sheath; according to the coarse screening main modal frequency, low-frequency guided waves are emitted, guided wave echo signals are collected, and low-frequency guided wave coarse screening is carried out to determine a suspected defect interval; and transmitting ultrasonic guided waves to the suspected defect interval according to the fine screening main modal frequency, accurately positioning the suspected defect interval, determining a comprehensive score through multi-feature weighting calculation, and determining a defect grade according to the comprehensive score. Low-frequency guided wave coarse screening is combined with wavelet transform and entropy verification, a suspected defect interval can be quickly locked, high-frequency fine screening extracts multi-dimensional defect features through variational mode decomposition, and accurate positioning of defect positions and scientific judgment of grades are achieved.

The invention belongs to the technical field of ground wire steel core detection, and particularly relates to a ground wire steel core detection system based on digital enabling, which comprises a detection device module, a data acquisition and processing module, a data analysis and intelligent identification module and a visualization and early warning platform module, the detection device module is integrated with a multi-mode sensing unit (a magnetizing device, a Hall array sensor, an ultrasonic guided wave transducer and an optical fiber sensing array) and a displacement positioning assembly, so that comprehensive acquisition and accurate positioning of damage signals are realized; the data analysis module is fused with a CNN-LSTM deep learning model to complete defect automatic identification and residual life prediction; the visual platform realizes hierarchical display and intelligent early warning based on digital twinning, and is also provided with a block chain module to guarantee data credibility; the system is compatible with portable inspection and on-line monitoring, is adaptive to the existing AEMR-I system, can improve the damage detection precision, the intelligent level and the operation and maintenance efficiency, and provides support for the safe operation of a power grid.

The invention discloses an ultrasonic guided wave damage ellipse imaging positioning method and equipment for a layer decreasing composite material laminated plate. The method comprises the following steps: S1, acquiring thickness change direction information of the laminated plate and position coordinates of an excitation transducer and a receiving transducer; s2, according to the material characteristic parameters, simulating and calculating the propagation time of ultrasonic guided waves transmitted from an excitation transducer to any point to generate a first theoretical propagation time map, and simulating and calculating the propagation time of the ultrasonic guided waves transmitted from any point to a receiving transducer to generate a second theoretical propagation time map to generate a second theoretical propagation time map; coupling influence of thickness change and material anisotropy on guided wave propagation is considered in the simulation process; s3, transmitting an ultrasonic guided wave signal, and extracting the actual flight time of a damaged wave packet; s4, calculating theoretical total propagation time, and determining a candidate area where damage exists; and S5, on the basis of repeated operation of the multiple groups of transducer pairs, taking a plurality of candidate region intersections to determine a final damage position. The objective of the invention is to solve the positioning error problem caused by the structural characteristics of a laminated plate in a traditional algorithm, and to realize more accurate damage detection and positioning.

The invention discloses a method for quantitatively evaluating the three-dimensional shape of a thinning defect in a plate under ultrasonic guided wave field undersampling scanning, belongs to the field of industrial nondestructive testing, and particularly relates to high-precision three-dimensional shape reconstruction and thickness loss quantification of a corrosion defect in a metal plate shell structure (such as aerospace skin, a pressure vessel wall, an oil pipeline and the like). According to the method, sparse sampling guided wave field reconstruction, full waveform inversion (FWI) and priori knowledge constraint are fused, Shannon sampling theorem limitation is broken through, efficient measurement of corrosion depth, contour and distribution under the conditions of a single excitation source and a limited view angle is achieved, and the method is suitable for rapid online detection in a complex industrial environment.

The invention discloses a pipeline defect detection method and system, and belongs to the technical field of pipeline defect detection. The pipeline defect detection method comprises the following steps: acquiring a preprocessed magnetic flux leakage signal and an ultrasonic guided wave signal; performing feature extraction on the signal to obtain a first feature subjected to multi-scale enhancement processing and a second feature subjected to convolution and attention mechanism processing; fusing by adopting a strategy including mutual information calculation and adaptive weight to obtain cross-modal fusion features; and performing multi-task detection and correction based on the fusion features to obtain a detection result indicating the type, the position and the size of the defect. According to the method, the limitation of single-mode detection can be overcome, and the accuracy of defect type identification, the positioning precision and the size quantification reliability are remarkably improved through dynamic weight distribution and physical constraint verification.

The invention discloses a product manufacturing process monitoring method and device based on a resin transfer molding process. The method comprises the following steps: monitoring a resin flowing front edge according to a first regression model and a second regression model when resin flows; inputting the monitored optical fiber signal into a pre-trained curing stage identification model to obtain a current curing stage when the resin is cured, and determining a current curing degree according to a fusion image obtained by the optical fiber signal and the ultrasonic guided wave signal; and determining a dry spot area according to the monitored optical fiber signal when the resin is cured, and determining the quantitative information of the dry spot according to the monitored ultrasonic guided wave signal in the dry spot area. In the resin injection process, the obtained ultrasonic guided wave signals and optical fiber signals are analyzed to monitor the flowing front edge, the curing degree and the dry spots of the resin, and through mutual verification of optical fiber monitoring results and ultrasonic monitoring results, the product manufacturing precision and the finished product quality are improved, and intelligent manufacturing of composite materials is achieved.

The invention provides an online monitoring method and device for the corrosion change condition of a storage tank bottom plate. The method comprises the steps that a to-be-monitored point of the storage tank bottom plate is determined, and an ultrasonic guided wave sensor probe used for monitoring the corrosion change condition of the to-be-monitored point and the distance between the to-be-monitored point and the ultrasonic guided wave sensor probe are determined; detection curves of the ultrasonic guided wave sensor probe are obtained regularly, and for two adjacent detection curves, difference processing is carried out on the latter detection curve and the former detection curve to obtain a change curve; wherein the abscissa of the detection curve represents the distance between a point in the ultrasonic guided wave transmission path and the ultrasonic guided wave sensor probe, and the ordinate of the detection curve represents the signal amplitude; and determining the corrosion change rate of the to-be-monitored point according to the value of the change curve when the value of the abscissa is the distance and the value of the corresponding previous detection curve. According to the online monitoring method and device for the corrosion change condition of the storage tank bottom plate, online monitoring of the corrosion change condition of the storage tank bottom plate is achieved.

The utility model discloses a piezoelectric sensor excitation symmetrical ultrasonic guided wave mode detection rail damage device belongs to piezoelectric sensor detection technical field, including rail waist testing mechanism, rail bottom testing mechanism and rail top testing mechanism, rail waist testing mechanism, rail bottom testing mechanism and rail top testing mechanism all include support, coupling piece, piezoelectric sensor and limiting component, and two limiting components are connected on the support symmetrically, and two limiting components are located at the both sides of track respectively, and the end of limiting component is connected with piezoelectric sensor, and coupling piece is fixed on the track symmetrically, and piezoelectric sensor is tightly pressed in the side of coupling piece through limiting component. The utility model can press the piezoelectric sensor stably on the different positions of track, and improves the precision of track detection.

The present application relates to a kind of carbon fiber composite material nondestructive testing methods based on piezoresistive nanofiber sensor, it includes the following steps: 1), preparation spinning solution;2), build electrospinning platform;3), preparation high frequency response piezoresistive nanofiber sensor;4), high frequency response piezoresistive nanofiber sensor is embedded in carbon fiber composite material board;5), to the carbon fiber composite material board vibration response test and ultrasonic guided wave test, to detect the damage condition of carbon fiber composite material board.The present application can guarantee that fiber sensor is embedded in carbon fiber composite material board, can guarantee that the nondestructive testing of carbon fiber composite material is realized under the premise of not affecting the mechanical properties of carbon fiber reinforced composite and not occupying carbon fiber composite material surface space.

The invention provides an ultrasonic guided wave frequency prediction method for corrosion prevention of a metal structural body in a marine atmospheric environment, which comprises the following steps of: acquiring data of surface stress generated when ultrasonic guided waves act on a metal pipeline under different excitation signals and the expelling effect of the surface stress on salt mist particles, and preprocessing the data to obtain a data set; a frequency prediction model is constructed, the frequency prediction model is based on MLP and comprises an input layer, a plurality of hidden layers and an output layer which are connected in sequence, and residual connection and activation functions are arranged in the hidden layers; inputting the data set into a frequency prediction model, and training through forward propagation and reverse propagation to obtain a trained frequency prediction model; and inputting the measured environment temperature data into the trained frequency prediction model to obtain a predicted frequency. The method shows excellent performance in experiments, and the accuracy of a predicted value is high, so that the optimal ultrasonic guided wave is kept, and the service life of metal and a surface coating is effectively prolonged.

The present application relates to ultrasonic guided wave detection instrument technical field, especially in a kind of non-contact ultrasonic guided wave detection instrument with one excitation multi-receiving function.The instrument includes analysis imaging unit, main control unit, excitation amplification unit, N channel switching unit, two groups of non-contact ultrasonic guided wave sensor and acquisition signal amplification unit, two groups of non-contact ultrasonic guided wave sensor are used to realize that different positions on pipeline produce multi-order mode ultrasonic guided wave respectively, and the reflected wave or transmission wave signal after the interaction of guided wave and defect in different directions is collected, the acoustic wave information representing the characteristics of defect is comprehensively obtained, so as to realize the high-precision imaging of the defect in the region to be detected.The stability and reliability of signal transmission are ensured by front-end excitation amplification and rear-end acquisition amplification.Non-contact detection is used, which has wide applicability and convenience.

The invention discloses a nondestructive testing method and system for corrosion defects of an anchor rod based on ultrasonic guided waves. The nondestructive testing method comprises the following steps: A, acquiring ultrasonic guided wave defect signals containing corrosion defect characteristics; b, performing modal decomposition on the ultrasonic guided wave defect signal to obtain an intrinsic modal component; c, effective modal components are screened, and de-noised intermediate reconstruction signals are obtained through signal reconstruction; d, sparse reconstruction is carried out on the middle reconstruction signal, and echo signal components representing different reflection interfaces are obtained; and E, determining the arrival time of a corrosion defect reflection echo in the sparse reconstruction signal according to the echo signal envelope peak value, and obtaining the position and length of the corrosion defect in the axial direction of the anchor rod by combining the propagation speed of the ultrasonic guided wave in the anchor rod. According to the method, the problems of strong noise interference, serious mode aliasing and difficulty in echo separation in ultrasonic guided wave detection of the corrosion defect of the anchor rod in the prior art can be solved, and accurate inversion of the position and length of the corrosion defect of the anchor rod is realized.

The application relates to a mode filter, a topology optimization method and an ultrasonic guided wave damage imaging artifact suppression method, relates to the field of ultrasonic detection and imaging, and the topology optimization method comprises the following steps: acquiring initial design parameters, generating an initial population, each chromosome individual in the initial population is coded by a binary logic matrix representing material distribution and meeting design constraints; a population is optimized by using a genetic algorithm, an adaptability function in the genetic algorithm is constructed based on a mode purity index and an energy transmission index, the mode purity index is the ratio of in-plane displacement integral in a transmission area in finite element simulation with the mode filter to total displacement integral, and the energy transmission index is the ratio of relative energy at a transmission end in the finite element simulation with the mode filter to relative energy of an S0 mode; and final optimized material distribution of the mode filter is output. Compared with the prior art, the application has the advantages of effectively suppressing background artifacts, giving consideration to mode regulation performance and substrate structure integrity and the like.

The invention relates to the technical field of pressure vessel intergranular corrosion detection, in particular to a nonlinear ultrasonic guided wave detection method for pressure vessel intergranular corrosion. The system comprises a signal generation and emission module, a signal acquisition and preprocessing module, a feature extraction and analysis module, a damage positioning and evaluation module, an optimization and calibration module and a data storage and visualization module. According to the invention, through cooperative work of the multi-band excitation signal and the distributed sensor array, the detection sensitivity and resolution are significantly improved; a nonlinear characteristic matrix and a multi-level decomposition capture material nonlinear effect are utilized to realize accurate positioning and evaluation; an adaptive parameter adjustment mechanism simplifies the operation process and reduces the detection cost; and a cloud database and a graphical interface are convenient for result storage and analysis. The intergranular corrosion can be efficiently and reliably detected, and a scientific basis is provided for the industrial field.

The welding pipe ultrasonic guided wave damage detection method based on modal conversion can realize real-time detection of global damage of the pipe, including the non-welding seam area and the welding seam area, can effectively avoid the influence of the pipe welding seam on the damage detection, and is particularly suitable for the needs of nondestructive testing of the welded pipe.

The application discloses a kind of based on ultrasonic guided wave's gas riser corrosion detection method and system, comprising: with the standard test block of the material and structural parameter consistent with the gas riser to be detected, prefabricate multiple different corrosion degree corrosion defects on standard test block, based on prefabricated corrosion defects, establish the calibration relationship between ultrasonic guided wave characteristic parameter and corrosion degree;Ultrasonic guided wave is emitted to the gas riser to be detected, and the echo signal after propagation via gas riser is received;Signal processing is carried out to echo signal to suppress interference and enhance effective signal component, and the feature parameter related to corrosion degree is extracted;The feature parameter extracted is compared with calibration relationship, and the corrosion degree of the gas riser to be detected is determined.The application realizes the non-destructive, long-distance, high-precision and quantitative detection of indoor gas riser corrosion, improves detection efficiency and accuracy.

The invention discloses a liquid viscosity measuring method based on a phase-locked loop algorithm. Liquid flows in the guided wave resonance element, the excitation and receiving coil is arranged on the surface of the guided wave resonance element in an attached mode, a permanent magnet is arranged beside the excitation and receiving coil, the temperature control module is connected with the guided wave resonance element, and the current sampling resistor is connected with the excitation and receiving coil in series. Ultrasonic guided-wave vibration is generated in a guided-wave resonant element through an exciting coil, voltage and current response signals of the resonant element are synchronously acquired by using a dual-channel synchronous sampling module, an impedance real part of the resonant element is accurately extracted according to the response signals, and accurate measurement of the liquid viscosity is realized by combining an established impedance-viscosity relation model. According to the invention, not only are the limitations of complex equipment, high cost and high requirement on sample volume of the traditional viscosity measurement method overcome, but also the problems of poor measurement stability, complex device manufacturing and difficulty in realizing online real-time monitoring under the working condition of strong noise or high damping in the existing method are solved.

The present application relates to the technical field of signal processing, and particularly relates to a pipeline guided wave signal processing method and system. The method comprises the following steps: acquiring multi-channel ultrasonic guided wave signals through a sensor array arranged circumferentially around a pipeline, and converting the signals into a frequency domain response matrix; calculating a circumferential amplitude distortion degree based on the amplitude distribution of the power spectrum of each channel; constructing a modal coupling matrix in combination with the circumferential amplitude distortion degree and an ideal pipeline theoretical wave number; generating a modal projection matrix by correcting a standard orthogonal modal matrix; and decomposing the frequency domain response matrix by using the projection matrix to separate a structure echo component and a defect signal component. The present application more accurately evaluates the influence of geometric defects such as ellipticity deviation, accurately models the energy exchange between modes and corrects the orthogonality assumption, suppresses modal energy leakage, improves the decomposition accuracy, effectively separates signals, solves the interference of coherent noise, and improves the accuracy and reliability of pipeline defect detection.

The invention provides an ultrasonic guided wave online defect detection method for a shell-and-tube heat exchanger and the heat exchanger. The method comprises the steps that a sensor array is permanently installed in a specific annular area of the outer surface of a tube plate; exciting and receiving the non-dispersion torsional guided wave to obtain an echo signal; performing noise reduction, frequency dispersion compensation and feature extraction on the signal; intelligently identifying defect types by using a pre-trained attention mechanism neural network model, quantifying the size and evaluating the confidence coefficient; using a fatigue or corrosion model to predict the remaining life based on the defect size and generating a report; a corresponding shell-and-tube heat exchanger is integrated with the detection system, the detection system comprises a sensor array and a built-in ultrasonic circuit, and through a network processing unit NPU special chip, an NB-IoT communication module and an embedded monitoring unit managed by an intelligent power supply, non-stop and online automatic defect detection and safety early warning of the heat exchanger are achieved.

The application discloses a railway point ultrasonic guided wave nondestructive detection method and a detection device, relates to the technical field of railway point nondestructive detection, and compares and judges the obtained real-time difference signals by using an abnormality analysis and judgment module; if there is no abnormality, the detection data is stored in a detection data database; if there is abnormality, the judgment result is sent to a prewarning reminding module, and meanwhile, the detection data is sent to an abnormality feedback verification model; the difference signals are predicted by using the abnormality feedback verification model, the predicted difference signals are obtained, the predicted difference signals are compared and analyzed with the real-time difference signals, and if the comparison is consistent, the comparison result is sent to the prewarning reminding module; when receiving the instructions of the abnormality analysis and judgment module and the difference signal analysis module, the prewarning reminding module performs point abnormality prewarning, the analysis result is verified by using the abnormality feedback verification model, and the influence of environmental factors on data acquisition is avoided to prevent misjudgment.

The invention provides an aero-engine blade missing data completion method based on ultrasonic guided wave detection, and the method comprises the steps: firstly, carrying out the projection of a three-dimensional aero-engine blade, and carrying out the grid division of a projection surface; arranging ultrasonic guided wave sensors on the grid points for detection to obtain a detection signal matrix; secondly, setting a missing rate to obtain an incomplete detection signal matrix, and obtaining a mask matrix according to the incomplete detection signal matrix; constructing a missing data completion network / discrimination network, and inputting the incomplete detection signal matrix and the mask matrix into the missing data completion network to obtain an output matrix; inputting the output matrix and the mask matrix into a missing data discrimination network to obtain an output result; and finally, carrying out iterative training on the two networks, and obtaining complemented detection data when the overall loss is kept stable. Based on the optimal network parameters, accurate detection data are complemented at data missing positions, and a reliable data basis is provided for subsequent detection of aero-engine blade defects.

This invention discloses a system and method for monitoring the hydrogen damage state of metals, comprising: a hydrogen charging device for electrochemically charging a plate-shaped sample of the same metal as the target metal that has not undergone hydrogen damage; a hydrogen permeation measuring device for converting hydrogen atoms permeating into the sample into hydrogen ions during the hydrogen charging process and measuring the current generated by the free electrons produced during the conversion process in real time to obtain a hydrogen permeation curve; and an ultrasonic measuring device for emitting ultrasonic guided waves to the sample during the hydrogen charging process and receiving the nonlinear response signal generated by the guided waves exciting ultrasonic waves inside the sample, and then performing cepstral analysis on the received signal to obtain the nonlinear coefficients at different time periods. Based on this, combined with the hydrogen permeation curve, the correlation between the nonlinear response signal and the degree of hydrogen damage is determined, and then the nonlinear response signal of the target metal is substituted into the correlation to obtain the hydrogen damage state inside the metal. This invention can monitor and evaluate the degree of hydrogen damage inside metals in real time.

The present application relates to a kind of rail abnormal condition identification system and method based on multi-source information fusion, comprising: the broadband vibration signal generated by the interaction of wheel and rail in train operation as passive excitation source;Through the multimode signal acquisition module installed on train body, acoustic wave or ultrasonic guided wave signal, track gauge data and train movement and braking state are synchronously collected;Signal processing and logic judgment module carries out the feature extraction and certainty threshold logic judgment based on physical mechanism to the multi-source heterogeneous data collected, and parallelly executes the fusion diagnosis of derailment risk, car abnormality and rail crack;When determining abnormal, result output module outputs the alarm information containing abnormal type and centimeter level mileage coordinate.The present application realizes the all-round monitoring of rail internal crack, external deformation and locomotive operating state, does not need external excitation source, response speed is fast, positioning is accurate, effectively improves the safety and operation efficiency of railway operation.

This invention discloses an ultrasonic guided wave excitation circuit for rail monitoring, comprising a signal generation module, a signal conditioning module, a power amplification module, and a boost output module, sequentially connected along the signal transmission direction. The power amplification module employs a monolithic integrated power amplifier chip for high-reliability amplification, and the boost output module uses a step-up transformer whose output energy is adjusted by changing the turns ratio. This circuit generates a preset optimized waveform through the digital signal generation module, which, after conditioning and amplification, ultimately outputs a high-voltage, clean excitation signal. It features high signal quality, strong anti-interference capability, flexible output energy adaptability to different monitoring distances, high system integration, and easy debugging, making it particularly suitable for long-distance online rail monitoring in harsh railway environments.

The invention relates to a method and a system for rapidly detecting defects of a large structural member based on air-coupled ultrasonic guided waves. The method comprises the following steps: S1, mounting a to-be-tested member; s2, adjusting the distance d1 of each transducer pair in the transducer linear array; s3, adjusting the distance d2 of each group of transducer linear arrays; s4, adjusting the incident angle of the air coupling probe; s5, setting and adjusting excitation voltage, software gain and a filtering frequency band, and conditioning a received signal waveform; s6, determining the total area of the scanning area; s7, the motion scanning structure scans along a preset path; and S8, generating a two-dimensional defect distribution diagram to complete defect detection. The method can realize large-area, rapid, accurate and visual defect detection of a large-scale to-be-detected structure, has the advantages of rapid identification and accurate positioning, has a good detection effect on a novel composite material, provides a new method for health monitoring of a large-scale structural member in the industrial field, and has significant innovativeness and application value.

The invention discloses a guided wave signal data driving proxy modeling method and system based on pulse response. The method comprises the following steps: acquiring a pulse response signal; adjusting the structural parameters of the structural member, obtaining pulse response signals corresponding to each parameter combination, and constructing a structured data set containing the structural parameters and the corresponding pulse response signals; constructing a neural network model, and training the neural network model based on the structured data set; and inputting structural parameters of a to-be-predicted structural member into the trained neural network model to generate a predicted pulse response signal, and performing convolution operation based on any ultrasonic guided wave input signal and the predicted pulse response signal to obtain an output signal after the input signal passes through the to-be-predicted structural member. The problems that an existing proxy modeling method is poor in complex scene adaptability, insufficient in continuous parameter space generalization and high in data set and training cost are solved, and efficient and accurate obtaining and outputting of the ultrasonic guided wave signals of the complex structural part are achieved.