2058 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.

The invention provides a metal material defect identification and analysis method and system based on a multiple detection technology, and relates to the technical field of metal defect detection, and the method comprehensively utilizes microscope detection and ultrasonic detection technologies to obtain surface topography data and internal structure data of a target metal material. And performing feature alignment and fusion processing on the two types of data through a multi-grid method to generate a unified feature distribution model, and establishing a mathematical solution model of ultrasonic wave field propagation based on the model. And determining the position, shape and size information of the potential defect by using the solved data, and generating defect positioning data containing three-dimensional coordinates and contour features. And extracting key defect information in combination with an edge detection algorithm, judging defect types by adopting a classification algorithm, and generating a detection result. According to the method, the problems of insufficient detection precision, high data fusion difficulty and low classification efficiency in the prior art are solved, and the applicability and reliability of a defect detection technology are improved.

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 relates to the technical field of nondestructive testing, in particular to a lead seal defect detection method based on a phased array ultrasonic testing technology. The invention discloses a lead seal defect detection method based on a phased array ultrasonic detection technology. The method comprises the following steps: acquiring surface three-dimensional data; carrying out data processing and modeling; phased array ultrasonic detection preparation; performing ultrasonic scanning; data analysis and defect identification; positioning and quantifying defects; and performing evaluation and report generation. According to the method, laser scanning is combined with phased array ultrasound, microscopic and macroscopic characteristics of the surface of the lead seal are obtained through laser scanning, an accurate three-dimensional geometric model is generated, the solid form of the lead seal is reproduced, a visual reference frame is provided for subsequent phased array ultrasound, and self-adaptive frequency adjustment and dynamic focusing control technologies are combined, so that the accuracy of the lead seal is improved. Different areas and heterogeneity of the lead sealing material are identified, the focusing position and depth of the ultrasonic beam are adjusted in real time, and the flexibility and accuracy of defect detection are improved.

The invention relates to the technical field of stone structure ultrasonic detection, in particular to a stone structure building detection method based on a concrete ultrasonic fault detection scanner, and the method comprises the steps: obtaining the initial signal intensity when an ultrasonic signal is transmitted by using the ultrasonic fault detection scanner; obtaining an ultrasonic reflection signal after the ultrasonic signal is reflected at each reflection point under each scanning layer, the intensity of the reflection signal after reflection, and the signal propagation duration; the method comprises the following steps of: obtaining a signal propagation time difference, a signal intensity difference, a signal difference index, a signal disorder degree, a defect evaluation coefficient, a seam recognition degree and a seam correction coefficient of each reflection point under each scanning layer, correcting the intensity of a reflection signal, performing three-dimensional reconstruction on a constructed tomography graph, and detecting internal defects of a stone structure building. According to the method, the interference of the reflection points on the splicing seams during stone splicing is reduced, the accuracy of detecting the internal defects of the stone structure building is improved, and the stability detection of the stone structure building is improved.

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 the technical field of pipeline detection, in particular to a guiding type pipeline welding seam ultrasonic detection device and a detection method thereof. Comprising a mounting base, and a pipeline limiting mechanism movably penetrates through one side wall of the mounting base; two groups of first supporting plates are symmetrically arranged at the edges of the two sides of the top of the mounting seat; and a pipeline guide mechanism and a welding seam detection mechanism are arranged in the first supporting plate. The ultrasonic probe is controlled to abut against the outer wall of the edge of the pipeline welding seam, then the conducting ring is controlled to drive the ultrasonic probe to move in the direction of the welding seam, and therefore the welding seam is comprehensively detected; according to the ultrasonic detection device, the ultrasonic probe can perform regular circular motion in a wave shape to detect a welding seam, meanwhile, the distance between the two sets of limiting rings can be adjusted according to needs so as to adjust the swing amplitude, the problem that the position of the probe deviates in the detection process is avoided, and therefore the using effect of the ultrasonic detection device is improved.

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 belongs to the technical field of welding seam detection, and particularly relates to a laser welding seam defect detection machine which comprises support plates, adjusting assemblies arranged between every two adjacent support plates, driving assemblies installed on the support plates and balancing assemblies arranged on one sides of the support plates. Wherein three groups of support plates are arranged in a circumferential array, a front-end support is fixedly mounted on one side of the long edge of each group of support plates, an ultrasonic detection probe, a dot matrix laser and a camera are sequentially mounted on the three groups of front-end supports, an electric control module is mounted on the top surface of each support plate, and a power supply module, a data analysis processing module and a control system are arranged in each electric control module. The device can automatically move on a reducing pipeline, perform positioning detection on a welding seam, and perform circumferential uninterrupted detection in the detection process, so that the detection precision is higher, a mode of combining laser detection and ultrasonic detection is utilized, displacement deviation is automatically corrected after reducing, the error probability is greatly reduced, unnecessary workload is avoided, and the detection efficiency is improved. The detection efficiency is 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 discloses a ring piece ultrasonic detection noise reduction and identification method and system and a computer storage medium. The method comprises the steps that a matched ultrasonic phased array probe is selected according to the shape and size of the cross section of a workpiece, and technological parameters are set and comprise at least one of the probe frequency, the number of array elements, the water layer height and the focusing depth; according to the selected ultrasonic phased array probe and process parameters, ring piece water immersion ultrasonic phased array detection is carried out, full-coverage scanning is carried out in a weld joint area, and the scanning position of the probe is recorded in real time through an encoder; in the scanning process, an ultrasonic image scanned by the phased array probe is collected in real time, and the ultrasonic image is transmitted to a pre-trained adaptive noise reduction YOLOv5 target detection model for defect recognition; and the rotating angle position of the ring piece is recorded in real time through an encoder, and when the target detection model finds defects, the defect position is recorded, and alarm information is generated. The method is suitable for ring piece ultrasonic detection noise reduction and recognition, the defect recognition accuracy can be improved, and the manual labor intensity is reduced.

The invention belongs to the field of material performance testing of mechanical structure strength, and particularly relates to an ultrasonic fatigue experiment monitoring method based on digital twinning. According to the method, on the basis of an ultrasonic fatigue testing machine platform, an ultrasonic fatigue digital twin model of a tested object is established by collecting frequency, temperature, load and other test data, and real-time online monitoring of ultrasonic fatigue and life prediction are carried out in combination with a fatigue life prediction model. Compared with a traditional test method, the method has the advantages that ultrasonic detection data and a digital twinborn model technology are combined, the fatigue life of the material is predicted and evaluated, the test efficiency is improved, the long-life test cost is reduced, and the accuracy and reliability of test data are improved.

The invention discloses a welding seam quality detection method and a welding seam detection system. The detection method comprises the following steps: acquiring an image of a detection area of the welding assembly by adopting a visual identification device; an ultrasonic detection device is adopted for scanning along the weld joint, and the ultrasonic detection area of the detection area is obtained; wherein the ultrasonic detection area is the welding area of the second welding piece and the concave bottom wall; comparing the ultrasonic detection area with an area threshold value; if the ultrasonic detection area is larger than or equal to the area threshold value, it is judged that the weld quality is qualified; if the ultrasonic detection area is smaller than the area threshold value, the welding seam quality is judged to be unqualified. The welding seam quality can be quantitatively evaluated, and the welding seam quality detection precision is improved.

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 provides a concrete bridge pile foundation risk detection method and system, and relates to the field of bridge pile foundations, and the method comprises the steps: through finite element analysis, based on the structure information and service information of a to-be-detected concrete bridge pile foundation, calculating the risk of the to-be-detected concrete bridge pile foundation; determining a plurality of risk detection points of the to-be-detected concrete bridge pile foundation and risk correlation coefficients among the plurality of risk detection points; arranging a risk detection device at each risk detection point; determining a plurality of ultrasonic detection positions of the to-be-detected concrete bridge pile foundation based on detection point state data collected by risk detection devices of the plurality of risk detection points and risk correlation coefficients among the plurality of risk detection points, and generating an ultrasonic detection scheme; according to the ultrasonic detection scheme, ultrasonic detection is conducted on the to-be-detected concrete bridge pile foundation, ultrasonic detection data of the to-be-detected concrete bridge pile foundation are obtained, risk analysis is conducted on the concrete bridge pile foundation, and the method has the advantage that nondestructive detection of the risk of the concrete bridge pile foundation is achieved.

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 detection, and provides a thick plate titanium alloy welding seam self-adaptive sensitivity ultrasonic detection method which comprises the following steps: designing a combined ultrasonic transducer, designing a detection system, testing and calibrating, testing a signal-to-noise ratio, scanning and evaluating. The detection system comprises a multi-channel ultrasonic detection collector, upper computer software and a combined ultrasonic transducer. Compared with the prior art, the self-adaptive sensitivity ultrasonic detection method for the thick plate titanium alloy welding seam has the advantages that the combined ultrasonic transducer is designed, thick plate titanium alloy welding seam detection and material acoustic performance evaluation are synchronously carried out, and the sound attenuation coefficient is fed back to a welding seam detection channel in real time by using upper computer software; and the detection sensitivity is adjusted in real time, so that the problem of inaccurate defect quantification caused by sensitivity difference due to non-uniform materials is solved, and accurate evaluation on the welding defects is realized.

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 relates to the technical field of pipeline detection, in particular to a buried oil and gas pipeline excavation defect detection device which comprises a fixed part, the fixed part comprises two fixed supporting rings, and movable detection parts are arranged on the two sides of the fixed supporting rings; the moving detection part comprises a plurality of moving rings, the moving rings are internally provided with grooves and fixedly connected with annular air bags, clamping assemblies slidably connected with the side walls of the moving rings are arranged below the annular air bags, moving wheels are arranged at the bottoms of the clamping assemblies, and pneumatic assemblies used for pneumatically propelling the moving rings to move are further arranged in the moving rings; the sides, close to the fixed supporting ring, of the movable rings are fixedly connected with detection assemblies, and the sides, away from the fixed supporting ring, of the movable rings are fixedly connected with cleaning assemblies. By designing the control system with the air pressure balance module, the buckling threshold value adjusting module and the ultrasonic detection module, flexible adaptation and high-precision detection of pipelines with different pipe diameters are achieved, and the detection efficiency and accuracy are improved.

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 relates to the technical field of ultrasonic detection, in particular to an ultrasonic detection method, system and device for integrated circuit plastic package. The method comprises the following steps: analyzing a distribution suspected index from a distribution position according to a proportion of a suspected defect area in an ultrasonic detection image of each sample and distance distribution of the suspected defect area and a module area, and analyzing an air hole characteristic index from internal distribution similarity in combination with a similar condition of ultrasonic signal fluctuation between pixel points in the area; obtaining a pore defect possible index; and correcting the air hole defect possible indexes by combining the overlapping expression of the suspected defect areas among the plurality of ultrasonic detection images, and obtaining the corrected possible indexes for air hole detection. According to the method, through the similarity characterization degree and the overlapping distribution degree of the defect features in the defect areas among the ultrasonic detection images of the multiple samples, the distinguishing accuracy of the electromagnetic noise and the pore defects is improved, the defect detection is more accurate, and then the optimization reliability of subsequent process parameters is improved.

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.