1557 results about "Ultrasonic testing" patented technology

The invention relates to the technical field of defect detection, and discloses a flange forging defect detection method and system. The method comprises the following steps: performing three-dimensional scanning and material acoustic characteristic measurement on a to-be-detected wind power flange to obtain layer partition sound isolation path data; generating an array element excitation control file of the double-array phased array ultrasonic detection system; applying the array element excitation control file to a double-array phased array ultrasonic detection system, and performing micro defect feature enhancement on a received echo signal to obtain a feature-enhanced signal data set; performing ultrasonic emission and data acquisition on the wind power flange to obtain a global detection data set; and inputting the global detection data set into the two-stage defect detection model for defect feature extraction and classification evaluation, and generating a defect detection evaluation report. According to the method, the detection rate and the classification accuracy of the micro forging defects are improved.

The invention discloses a railway track damage detection method, and belongs to the technical field of railway track detection. According to the method, an image acquisition module and an ultrasonic detection module are installed at the bottom of a track detection vehicle, the detection vehicle is controlled to run, and track top face and side face image sequences and ultrasonic reflection signals are acquired; preprocessing the image, and respectively inputting the image into a deep convolutional neural network model and a support vector machine classifier to obtain a crack identification result and a wear level; processing an ultrasonic reflection signal, and judging a layering defect; and finally fusing the data, marking a damage position and generating a structured detection report. According to the method, the problems of incomplete detection, low precision and the like in the existing railway track damage detection are solved, efficient detection of track surface cracks, side abrasion and internal layering defects is realized through collaborative acquisition of the multi-modal sensor, intelligent algorithm processing and data fusion, and the comprehensiveness and reliability of detection are improved.

The invention relates to the technical field of data processing, and discloses a steel structure welding seam quality ultrasonic detection method and system. The method comprises the following steps: scanning a welding seam to obtain digital parameters, constructing a virtual model to generate an ultrasonic response database, optimizing a detection parameter forming scheme, executing distributed acquisition to obtain a signal matrix, extracting defect features by using a neural network, and outputting a digital detection report through transfer learning. According to the method, automatic optimization of detection parameters and accurate extraction and intelligent analysis of defect features are realized, the accuracy, efficiency and reliability of detection are improved, and the dependence on artificial experience is reduced.

An ultrasonic inspection robot for a threaded connection structure of a rotor internal cavity includes a main rack, a clamping module, a lifting module, a rotating module, a telescopic module and a probe buffer module. The present invention can be operated in a narrow, long and strongly restricted space, realizes the inspection of the nut that is inaccessible to the naked eye by carrying testing probes realizes the automated measurement function of placement and pressing of the carried probes, the switching between different test points, and all the points to be measured in an axial direction, and the deformation action of the device, realizes the extension and reduction of the axial and radial dimensions of the device, and completes all functions of placing and taking out the whole device. Moreover, the above functions can be realized only through one device.

The invention relates to the technical field of nondestructive testing, and discloses a steel structure weld defect ultrasonic detection and identification system. A data acquisition module of the system acquires an original ultrasonic signal of a steel structure welding seam through ultrasonic detection equipment and acquires geometric attribute data of the welding seam; the model construction module constructs a welding seam three-dimensional digital model based on the data; a feature extraction module performs feature mining on the three-dimensional digital model and extracts a weld defect feature index set; the difference analysis module carries out deviation calculation on the characteristic index set and a reference index set in a standard welding seam characteristic database, and an abnormal area is identified; the risk assessment module calculates a defect sensitivity index according to the abnormal region in combination with real-time environmental parameters, and assesses a defect risk level; and the report generation module formulates a detection scheme according to the defect risk level, generates a detection instruction, executes ultrasonic scanning, collects performance data and generates a defect detection report. The system has the advantages of high detection precision, high reliability, automatic and standardized process and the like.

The invention provides a double-mechanism cooperative type curved surface component water immersion ultrasonic intelligent detection method and system, and relates to the technical field of ultrasonic detection, and the method comprises the following steps: scanning a workpiece by using a double-mechanism water immersion ultrasonic detection system, collecting and processing an ultrasonic echo signal, and generating an ultrasonic C scanning image. And performing defect identification on the ultrasonic C scanning image by using the constructed multi-scale feature fused deep convolutional neural network model to obtain the type, position, size and confidence of the defect. Quantitative evaluation is carried out based on the defect recognition result, a report is generated, and meanwhile visual display and database management of the defect recognition result are achieved. Through double-mechanism cooperative scanning and deep learning intelligent identification, the precision and efficiency of curved surface component defect detection are improved, and automatic identification, quantitative evaluation and visual display of defects are realized.

The invention relates to a lightweight component surface defect quantitative evaluation method, system and device, and the method comprises the steps: obtaining a multispectral surface image, laser three-dimensional data and ultrasonic detection data of a lightweight component, and carrying out the fusion registration based on a preset multi-sensor synchronization protocol, and obtaining a component joint data set; performing dynamic pruning analysis on the component joint data set to obtain geometric contour features, and performing internal feature extraction on the component joint data set to obtain internal abnormal response features; stress gradient distribution data and volume ratio parameters are carried out on the geometric contour features and the internal anomaly features; and obtaining an original working condition data set of the lightweight component, carrying out service working condition coupling analysis on the multi-dimensional prediction matrix, and carrying out multi-dimensional quality l parameter identification to obtain component comprehensive quality information. According to the method, the morphology mechanical coupling feature extraction precision of composite defects such as cracks and holes can be improved.

The invention relates to the technical field of cylindrical lithium ion battery production, and discloses a method for detecting insufficient welding of a cylindrical lithium ion battery, and the method comprises the following steps: S1, appearance inspection; s2, initial internal resistance benchmark test; s3, applying a short-time large-current pulse to the battery by using a pulse generator, simulating an actual load condition, and recording an instantaneous voltage drop and current response curve of the voltage of the battery end during the pulse period; s4, performing infrared thermal imaging identification and data processing; s5, learning the picture and establishing a model; s6, comparing the test picture and the data with the model; s7, dynamic internal resistance calculation; s8, cold solder joint query and sorting processing; and S9, retesting the electrical performance. According to the invention, the technologies of dynamic internal resistance measurement, nondestructive X-ray or ultrasonic detection, rate discharge test and the like are adopted, so that efficient, accurate and nondestructive detection of the cold solder joint of the cylindrical lithium ion battery is realized, and the production efficiency and the detection precision are remarkably improved.

The invention discloses a bearing defect detection method and system based on machine vision and ultrasonic detection, and particularly relates to the technical field of industrial automatic detection, and the method comprises the steps: S1, a synchronous collection module: carrying out pulse triggering synchronous collection, and generating a time-space reference table; s2, a feature extraction module: performing image noise reduction segmentation and ultrasonic frequency domain decomposition, and outputting a defect feature vector; s3, a fusion identification module: performing cross-modal feature alignment fusion to generate a defect classification conclusion; s4, a size measurement module: performing contour fitting to calculate inner and outer diameters, and outputting a size deviation value; and S5, a comprehensive judgment module: carrying out threshold comparison logic judgment, and generating a multi-modal detection report. According to the method, a space-time reference is established through an encoder, images are segmented in a self-adaptive mode, features are extracted through wavelet decomposition ultrasound, feature weights are re-calibrated through a parallel network and an attention mechanism, composite defects are recognized through cross-modal fusion, comprehensive judgment is conducted in combination with dimensional deviation, and a multi-dimensional quality evaluation system is achieved.

The invention relates to the technical field of composite material detection, in particular to a fiber-reinforced thermosetting thermoplastic composite structure interface quality detection method and system.The method comprises the steps that vibration excitation is applied to a target area of the surface of a to-be-detected sample, and the amplitude of the excitation is lower than the damage critical value of a weak bonding interface; a dynamic response signal perpendicular to the interface is collected in a vibration field non-diffusion area of the excitation point of the target area; performing frequency domain transformation on the dynamic response signal, and separating a fundamental frequency component and at least one high-order harmonic frequency component; according to the nonlinear enhancement effect of the high-order harmonic frequency component relative to the fundamental wave frequency component, whether the weak bonding defect exists in the target area or not is judged. According to the method, the technical bottleneck that the dynamic evolution process of the weak bonding defect of the composite material interface is difficult to capture in real time is effectively solved, sensitive response to the microdefect is realized through a nonlinear harmonic characteristic enhancement effect, and the recognition precision of traditional ultrasonic detection is improved.

The invention relates to the technical field of concrete testing, in particular to a concrete testing method which comprises the following steps: manufacturing a plurality of groups of standard-size concrete test pieces according to a preset concrete mix proportion, and respectively placing the standard-size concrete test pieces under a simulated curing condition and a standard curing condition for curing in a preset curing period to form a first test group and a first control group; based on a plurality of detection points, carrying out a rebound test and an ultrasonic test on the concrete test pieces in the first test group, and determining a high-frequency ultrasonic section to determine an ultrasonic attenuation coefficient of a single concrete test piece, according to the ultrasonic propagation speed, the ultrasonic attenuation coefficient and the detection rebound value, constructing a concrete strength-based correction model to obtain the comprehensive compressive strength of the concrete test pieces in the first test group, and determining the standard compressive strength corresponding to the concrete test pieces in the first control group, and determining an initial influence coefficient of the simulated maintenance condition according to the comprehensive compressive strength and the standard compressive strength. The compressive strength of the concrete structure is effectively tested.

The invention relates to the technical field of ultrasonic detection, and discloses an ultrasonic scanning path optimization and three-dimensional reconstruction method, device, equipment and medium, and the method comprises the steps: positioning a key mark point of a target area, generating an initial scanning path, and controlling an ultrasonic probe to move along the initial scanning path to collect first ultrasonic image data, extracting target structure features to construct an initial three-dimensional point cloud model; establishing a surface projection model; fitting to generate a surface profile curve and calculating the tangential direction of a sampling point; optimizing the orientation of an ultrasonic probe based on the tangential direction to generate an optimized scanning path; and reconstructing a final three-dimensional model. According to the invention, through key mark point positioning and incident direction optimization based on the tangential direction, the scanning path of the probe is enabled to be adaptive to curvature change of the target area, and through combination of real-time contact force adjustment and multi-stage image data acquisition, three-dimensional point cloud space coverage and imaging consistency are improved, and high-precision three-dimensional reconstruction of a complex anatomical structure is realized.

The invention discloses a hydropower station diversion tunnel longitudinal crack depth detection method, which comprises the following steps: arranging ultrasonic measuring points above and below a diversion tunnel longitudinal crack to obtain a reinforced concrete sound velocity representative value; arranging ultrasonic measuring points within the length range of the crack; performing ultrasonic detection, and judging the depth of the crack through ultrasonic waves; adjusting the position of the ultrasonic measuring point according to the depth of the fracture until the ultrasonic shape is in a suitable state; and calculating the depth of each detection point of the longitudinal crack. According to the technical scheme, by means of the method for detecting the longitudinal crack depth of the reinforced concrete in the diversion tunnel of the hydropower station through the ultrasonic waves, crack depth detection and calculation of the circular tunnel are completed, and in order to judge the development condition and the stability state of the crack, the crack depth can be regularly detected in the overhaul period of a hydropower station generator set; therefore, monitoring of longitudinal crack expansion and extension is realized.

The invention discloses an underground space surrounding rock excavation damage area testing method, which belongs to the technical field of rock mass damage testing, and comprises the following steps: sampling rocks with different depths, carrying out ultrasonic testing, and determining rock sample attenuation characteristics and wave velocity; determining a comprehensive damage index range of the rock samples with different damage grades; then, sensors are arranged in the excavation process to collect ultrasonic and acoustic emission data; then, an initial calculation model is constructed, and a surrounding rock three-dimensional wave velocity model is obtained through inversion of collected data; and finally, determining a damage grade according to the comprehensive damage index, and marking in the model to realize damage area testing. According to the method, the mapping relation between the damage degree and the wave velocity change is established, the comprehensive damage index range threshold value of different subareas is provided, quantitative and gradable classification is achieved, the three-dimensional wave velocity model is inversed based on test and monitoring data, and three-dimensional presentation and grading labeling of the damage area are achieved.

The invention relates to the technical field of ultrasonic detection, in particular to a building steel structure strength ultrasonic phased array nondestructive testing method which comprises the following steps: acquiring morphology data of the surface of a building steel structure; analyzing coating thickness distribution and weld surface roughness of the surface of the building steel structure, and constructing a surface information matrix; automatically adjusting ultrasonic wave beam parameters of the ultrasonic phased array by using the self-adaptive parameter regulation and control model, and performing ultrasonic phased array detection to obtain a preliminary ultrasonic echo signal; adopting an echo signal compensation model to perform secondary compensation on the preliminary ultrasonic echo signal through the difference between the reference signal and the preliminary ultrasonic echo signal to obtain an optimized ultrasonic echo signal; fusing the optimized ultrasonic echo signal, the morphology data and the surface information matrix, and performing defect detection on the building steel structure by using the building steel structure detection model; evaluating a detection result, and dividing a confidence level; and carrying out local re-detection and parameter adjustment on the low-confidence region to realize closed-loop optimization.

The invention relates to the technical field of nondestructive testing, in particular to a weld joint ultrasonic testing parameter optimization method based on particle swarm optimization, which comprises the following steps: acquiring a weld joint path three-dimensional coordinate sequence, combining structure prior and boundary conditions, removing abnormal points by self-matching cubic splines to regulate and control node density, generating a curvature data set, and optimizing weld joint ultrasonic testing parameters according to the curvature data set. Smooth processing is carried out to extract curvature derivative variation; a key section is screened; a parameter set is constructed and dense sampling is carried out; feature points are detected to generate a focusing area, a matching degree function is established to execute parameter optimization, and an optimal combination set is output. According to the method, on the basis of welding seam path coordinates and structure prior, self-matching cubic spline interpolation is improved to eliminate abnormal regulation density, curvature data is generated, filtering and derivative screening focusing sections, Latin sampling difference distribution parameters and derivative feature extension paths are performed, a matching degree function is constructed to drive particle swarm optimization, and parameter reinitialization matching energy is performed; the signal-to-noise ratio and the detection rate are improved, and the resource allocation efficiency is optimized.

The invention discloses a panel vertical seam water stop structure repair effect evaluation method, which comprises the following steps of: firstly, synchronously obtaining surface crack and internal defect data through cooperative detection of infrared thermal imaging and ultrasonic flaw detection; and carrying out space alignment on point cloud data generated by three-dimensional laser scanning and an ultrasonic detection result, and establishing a BIM model containing a crack three-dimensional form. A practical engineering environment is simulated in a laboratory to carry out material accelerated aging and test key indexes such as an elastic recovery rate, a base surface state is evaluated through a temperature and humidity sensor array in a construction stage, a six-axis grouting robot is adopted to execute accurate filling, a curing process is monitored by a synchronous pre-embedded optical fiber sensor, and after aging is simulated by combining a hydraulic test with climate, a construction period is shortened. A distributed optical fiber network is used for continuously collecting deformation data, a comprehensive evaluation model is constructed based on mechanics, durability and sealing indexes, and finally material selection and process parameters are optimized through machine learning.

The invention discloses a defect detection system for a metal-composite material mixed structure device. The defect detection system comprises an industrial control computer, a mechanical scanning arm, a polarization detection probe, an ultrasonic detector assembly and a power supply, the invention further provides a defect detection method for the metal-composite material mixed structure device. The defect detection method specifically comprises the following steps: acquiring polarization image information of the metal surface; solving polarization image parameter information; carrying out surface defect detection; metal internal ultrasonic detection information is obtained; performing internal defect detection; and performing multi-mode data fusion detection. According to the invention, two information sources with complementary advantages, namely polarization and ultrasound, are selected as detection information sources of the multi-modal detection method, so that all-directional defect detection and visualization on the surface-interior of the metal-based composite material mixed structure device are effectively realized; and a feasible technical method is provided for engineering application of polarized light / phased array ultrasonic multichannel integrated detection.

The invention discloses a magnetoacoustic coupling detection system and method for pipeline defect detection, and relates to the technical field of pipeline nondestructive detection. The system comprises a pipeline defect detection module, a magnetofluid driving module, an auxiliary moving module, a signal acquisition module, a data processing module and a data transmission module. The pipeline defect detection module comprises a magnetic flux leakage detection unit and an ultrasonic detection unit; the magnetofluid driving module comprises magnetofluid and an electromagnetic excitation device; the auxiliary moving module comprises a plurality of driving wheels tightly attached to the inner wall of the pipeline. The signal acquisition module comprises a data acquisition unit and a data storage unit; and the data processing module is used for processing the acquired magnetic excitation parameters, the magnetic leakage signals and the sound wave sensing data. According to the invention, the technical problems of low defect identification precision, complex use of a coupling agent, insufficient real-time data processing capability and the like existing in a single detection mode in the prior art can be solved.

The invention relates to the technical field of ultrasonic scanning imaging, and discloses an ultrasonic robot real-time trajectory planning method and system based on an ultrasonic image. The trajectory planning method is applied to the ultrasonic scanning robot and specifically comprises the following steps that S101, an area where a target tissue is located is obtained, continuous scanning is carried out, an image of a cross section is obtained in real time, meanwhile, preliminary positioning of an ultrasonic probe is completed, and each frame of collected image and posture data of a current mechanical arm are synchronously recorded; and S102, carrying out image segmentation processing on the obtained image of the cross section, identifying a target structure region represented in each frame of image, accurately separating the target structure region from a complex background, obtaining the target segmentation of each frame of image, and then entering a spatial modeling stage. According to the method, the quality and robustness of the ultrasonic diagnosis image are improved by using the advantages of high learning efficiency and good generalization of the deep learning model, and the problem of poor online real-time adjustment capability in the current ultrasonic detection technology is solved.

The invention provides an automobile dashboard cross beam support strength detection device, which comprises a smearing assembly and a driving mechanism, the smearing assembly comprises a smearing shell, the smearing shell is used for accommodating a coupling agent and smearing the coupling agent on a cross beam support, the smearing shell is internally provided with a first chamber, a second chamber and a third chamber, the volumes of which can be adjusted, and the driving mechanism is used for driving the first chamber, the second chamber and the third chamber to rotate; the volume of the cavities and the liquid outlet amount of the coupling agent are in positive correlation, and the first cavity, the second cavity and the third cavity correspond to an upstream area, a middle flow area and a downstream area of the welding area in sequence. And when the area, attached to the welding machine, of the smearing shell inclines, the driving mechanism enables the volumes of the second cavity, the first cavity and the third cavity to be sequentially reduced according to the inclination angle of the welding area. Therefore, the interior of the smearing shell is arranged to be the cavity with the adjustable volume, so that the coupling agent in each area of the welding area can be uniformly distributed, and stable transmission of ultrasonic detection signals is ensured.

The invention relates to the technical field of ultrasonic detection, and discloses an ultrasonic-based weld defect detection method and system.The method comprises the steps that a historical database is established, ultrasonic echo signals are traversed in the historical database, a reuse defect strategy or an ultrasonic verification strategy is determined according to the traversal result, and when the reuse defect strategy or the ultrasonic verification strategy is determined, the ultrasonic verification strategy is determined; determining a first ultrasonic result based on the echo delay and the echo intensity, determining a second ultrasonic result based on the ultrasonic echo signal and the ultrasonic feature model, determining whether the weld joint to be detected has defects or not according to the first ultrasonic result and the second ultrasonic result, and performing Fourier transform on the ultrasonic echo signal to obtain the weld joint to be detected. The defect type of the weld joint to be detected is determined based on the ultrasonic characteristic spectrogram, the attenuation result is determined based on the three-dimensional model and the metal sample and written into the simulation database of the simulation environment, the defect type is verified based on the relation between the ultrasonic characteristic spectrogram and the simulation spectrum curve, and the reliability and stability of ultrasonic detection are ensured.

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 the technical field of ultrasonic detection, in particular to an ultrasonic imaging method and system for ultrasonic detection of a titanium alloy bar, and the method comprises the steps: obtaining an ultrasonic detection signal of each detection point; the ultrasonic detection signals of the detection points form an initial imaging area according to the combined probing path, and a state label about amplitude deviation in the initial imaging area is recognized; performing conditional mapping on the frequency spectrum difference of each detection point and the interval time during detection by using the state label of the initial imaging area to obtain the difference classification of each detection point; according to the difference classification of each detection point, identifying the difference guidance of the current detection path, converting the corresponding detection point into a displacement component of the surface of the titanium alloy bar according to the combination position of each detection point in the difference guidance, analyzing partial data of a minimum value, a minimum value inflection point and an offset standard value of the displacement component distribution, and calculating the displacement of the titanium alloy bar. Identifying the surface defect form of the titanium alloy bar; and the titanium alloy bar defect identification accuracy and efficiency are realized.

The invention relates to the technical field of titanium alloy detection, and discloses a titanium alloy wire performance detection method, equipment and system. The method comprises the following steps: acquiring real-time force value displacement data of a tensile test and echo signal data of ultrasonic detection, and processing to obtain smooth force value displacement data and spectrum characteristic parameters; performing feature layer fusion on the yield strength, the tensile strength, the peak frequency and the amplitude attenuation rate to construct a first multi-dimensional feature matrix; inputting a pre-trained deep belief network model, and predicting mechanical properties such as elongation and hardness value; and comparing with a preset threshold value, marking unqualified items and generating a detection report. According to the method, through multi-source data fusion and advanced algorithm processing, the comprehensiveness and accuracy of detection are improved, efficient evaluation of the performance of the titanium alloy wire is achieved, and the method is suitable for the strict detection requirements for the quality of the titanium alloy wire in the fields of aerospace, medical instruments and the like.

The utility model relates to the technical field of phased array ultrasonic detection, in particular to a phased array ultrasonic detection pipeline scanning device which comprises a detection equipment body, a detection probe and a track ring, and the track ring is provided with a movable assembly used for carrying the detection probe for automatic detection. The movable assembly comprises a movable frame arranged on the track ring and used for driving the detection probe to move, and two pulleys and a transmission part used for driving the movable frame to move are arranged between the movable frame and the track ring. By arranging the movable assembly, the motor can be started to drive the gear to rotate on the gear ring, the movable frame does circular motion on the track ring under the cooperation of the guide groove and the pulley, and the detection probe is driven by the long bolt and the electric push rod to move and scan on a welding seam on the surface of a pipeline, so that the welding seam is detected; the long bolt is arranged, so that the position of the detection probe is adjusted under the action of the guide rod and the electric push rod in the rotating process, and the position of the detection probe is located at the optimal welding seam detection position.

The invention discloses a non-convex contiguous group sparse variational filtering hyper-parameter adaptive calculation method, which comprises the following steps of: selecting a reference signal according to ultrasonic signal characteristics, and determining the size of a group sparse group through a specific formula in combination with a sampling frequency and a probe frequency; after interference removal is carried out on the ultrasonic signal, a scattering noise standard deviation is calculated based on the reference signal, and a regularization parameter is obtained in combination with a formula; calculating a penalty factor; when the detection sound path distance is less than 1000mm, adopting global filtering; when the sound path distance is detected to be larger than 1000 mm, local filtering is adopted, a punishment intensity reference value is estimated based on the noise level, the reference value is corrected in combination with the signal-to-noise ratio, and then a formula is substituted to calculate a punishment factor coefficient and a final punishment factor; in the iteration process, the relative variable quantity of the cost function is used as a convergence criterion, iteration is stopped when the variable quantity is smaller than a preset threshold value, and efficient and stable filtering is ensured; the method completely meets the engineering application requirements of industrial ultrasonic detection.

The invention belongs to the technical field of metal crack detection, and discloses a metal microcrack ultrasonic detection method, which comprises the following modules: an ultrahigh frequency composite array probe with a center frequency dynamic adjustable range of 5-50 MHz; the dual-mode excitation and receiving module is used for independently generating a pulse reflection mode excitation signal and a diffraction mode chirp frequency modulation signal; the phase-controlled synthetic aperture dynamic focusing module is used for realizing + / -60-degree deflection and sub-wavelength level focusing of acoustic beams; the nonlinear harmonic enhancement module is used for exciting a crack nonlinear effect by superposing 1-2MHz fundamental waves; and a time-space-frequency three-domain data fusion module. According to the method, signal-to-noise ratio collapse caused by the diffraction effect in a traditional method is overcome, more importantly, the system has low-frequency penetrability and high-frequency resolution at the same time due to 80%-120% of broadband coverage of chirp frequency modulation signals, the diffraction signal gain is increased by 20 dB or above, a near-surface blind area is compressed to be within 0.2 mm, and the system can be applied to the field of radar imaging. And the core pain point of missing detection of the near-surface microcracks of the thin-wall component is solved.

The invention relates to the technical field of ultrasonic detection, and provides an aero-engine fuel control valve leakage amount ultrasonic detection method, which forms a coherent technical link through leakage ultrasonic signal acquisition, leakage signal separation, leakage feature extraction, leakage area positioning, offset compensation and cross validation of a sensor, and the links are mutually verified and optimized. A leakage signal is separated through a dynamic threshold value, the identification degree of a deep belief network is enhanced through multi-dimensional features, environment interference is compensated and corrected through working condition parameters, positioning deviation caused by single-link error accumulation in a traditional method is effectively restrained, accurate capturing and positioning of a micro leakage signal are achieved, and the method is suitable for large-scale popularization and application. The leakage thermodynamic diagram integrates leakage rate grading, coarse positioning area and micro leakage point information, the analysis and decision-making time of maintenance personnel is greatly shortened through a visual presentation mode, and rapid interpretation of fault positions and severity is achieved.

The invention relates to a GIS (Geographic Information System) basin-type insulator defect detection method, electronic equipment and a storage medium, belongs to the technical field of intelligent image identification and processing of power equipment, and solves the problem of how to improve the accuracy of GIS basin-type insulator defect detection. The method effectively improves the resolution and information integrity of defect images, constructs a MobileNetV2 and YOLOv11n lightweight network structure for the technical bottlenecks of large FMC data volume and complex imaging calculation, achieves the intelligent closed-loop process from defect identification, positioning and classification to segmentation evaluation, achieves the automatic identification and geometric quantity extraction of defect areas, and improves the accuracy of the detection result. A data support is provided for subsequent early warning judgment and decision making; according to the method, the ultrasonic detection identification precision and the imaging quality are effectively improved.