558 results about "Non destructive" patented technology

The invention discloses an irregular particle three-dimensional shape measurement device and method based on speckle imaging, and belongs to the field of irregular particle three-dimensional shape measurement, and the irregular particle three-dimensional shape measurement device comprises an irregular particle shakeout device which is used for enabling irregular particles to fall in a sparse free falling body form, and is used for forming lamellar laser vertical to the falling direction of the irregular particles, the laser sheet generating module is used for forming complete speckle distribution on the surfaces of the irregular particles; the laser sheet generating module is used for generating a laser sheet, the multi-view image collecting module is used for collecting speckle distribution on the surfaces of irregular particles in a multi-view mode and forming speckle images, the synchronous control system is used for controlling the laser sheet generating module and the multi-view image collecting module and synchronizing the time of the laser sheet generating module and the multi-view image collecting module, and the three-dimensional reconstruction processing unit is used for obtaining three-dimensional shape data of the irregular particles according to the speckle images. According to the invention, the irregular particles can be rapidly, non-destructively and in-situ measured so as to meet the requirements of aeroengine erosion research on the precision, efficiency and integrity of irregular particle data.

The invention discloses an intelligent and efficient detection method for concrete-filled steel tube arch bridge arch rib void. The method comprises the following steps: 1, detecting a full bridge arch rib through laser scanning, obtaining three-dimensional point cloud data, identifying a suspected void area, and generating a bridge three-dimensional model; 2, detecting a full-bridge arch rib through infrared thermal imaging, recording a temperature distribution diagram, identifying a temperature abnormal region, and confirming a suspected void region; 3, echo signal characteristics of the suspected void area are detected through ultrasonic waves, and the specific position, depth and range of void are determined; 4, carrying out fusion analysis on laser scanning, infrared thermal imaging and ultrasonic detection data to generate a three-dimensional void distribution model, and generating a comprehensive detection report in combination with multi-source data; and 5, the arch bridge is monitored in real time, trend analysis and prediction are performed in combination with historical data, and a void expansion early warning mechanism is formed. According to the method, the void position, depth and range of the arch rib can be detected in a high-precision and non-destructive manner, and a reliable guarantee is provided for bridge safety.

The invention discloses a fire-fighting non-destructive detection method based on multi-modal detection, and relates to the technical field of fire-fighting engineering, and the method comprises the following steps: carrying out the rapid scanning of fire-fighting equipment through an ultrasonic array, analyzing and positioning a suspected defect region based on a time domain reflection signal, and generating a three-dimensional coordinate mapping model; and performing multi-angle X-ray projection acquisition on the positioning area, and generating an internal structure cross-sectional image through a three-dimensional reconstruction algorithm. According to the fire-fighting non-destructive detection method provided by the invention, by integrating various technical means such as ultrasonic array scanning, X-ray tomography, thermal imaging analysis and microwave sealing detection, comprehensive and accurate identification of potential defects of fire-fighting equipment is realized, and the dimensionality and precision of defect detection are improved; the structural integrity of the equipment is kept to the maximum extent, extra risks caused by destructive detection are avoided, and the reliability and accuracy of detection are improved through a data fusion algorithm.

The invention provides an on-line automatic test method for the compressive capacity of a corrugated carton, and belongs to the technical field of corrugated carton production. A micro-deformation loading system is constructed to apply a test load which does not exceed 10% of the expected maximum bearing capacity, and a laser displacement sensor array is adopted to measure micro-deformation displacement data of six surfaces of the carton; and synchronously acquiring acoustic emission signals and extracting spectrum characteristic parameters. Micro-deformation data is analyzed based on a carton fiber structure physical mechanism model, stress field distribution is calculated, analysis is carried out in combination with a hierarchical attention carton strength evaluation model, a rigidity coefficient is calculated and compared with a reference threshold value, a structural weak area is identified through a strain energy distribution diagram, and a damage risk index is quantified. And comprehensively evaluating the compressive strength prediction value and the confidence interval of the corrugated carton, and outputting a prediction result, thereby realizing accurate evaluation of the compressive strength of the corrugated carton under a non-destructive condition.

The invention relates to the technical field of metal material heat treatment quality detection, in particular to a metal material rapid annealing effect detection method based on acoustic response, which comprises the following steps: step 1, acoustic excitation and synchronous acquisition; step 2, multi-physics field coupling compensation: calculating the phase compensation amount of the vibration signal based on the temperature distribution data and the acoustic characteristic temperature dependence of the material; the method comprises the following steps: acquiring an environment vibration frequency spectrum through a production line mechanical vibration monitoring device, and separating an excitation response component from an original vibration signal by adopting adaptive filtering; 3, annealing sensitive feature extraction; 4, dynamic quality mapping and control: inputting the real-time feature vector into a pre-trained machine learning model, and outputting a recrystallization proportion and a grain size; and when the output parameter exceeds the process threshold value, the control parameter adjustment of the annealing furnace is triggered. Through a non-destructive and accurate acoustic monitoring technology, the annealing effect of the metal material can be efficiently and accurately monitored in a high-speed, high-noise and strong-interference industrial environment.

The invention discloses a method and system for detecting abnormal welding spots in the spot welding process. The method comprises the steps that a time sequence data sequence collected in real time in the welding process is obtained; calculating a first-order difference sequence of the time sequence data sequence; screening a target data segment representing a stable trend based on the first-order difference sequence; performing linear fitting on the first K data points of the target data segment to obtain a first trend direction; performing linear fitting on the last K data points of the target data segment to obtain a second trend direction; calculating the variable quantity of the first trend direction and the second trend direction; and when the variable quantity exceeds a preset threshold value, it is judged that welding is abnormal, and an alarm is triggered. The stable trend section is screened through the differential sequence, noise interference is effectively eliminated, and it is ensured that the quality criterion is based on reliable data. And whether the welding spot is abnormal or not is quickly and accurately judged, so that real-time and non-destructive spot welding quality on-line monitoring is realized.

Methods involving physics-informed deep learning to help solve inverse problems of solid materials / structures related to unknown geometry include (1) identifying and characterizing unknown materials / structures and defects with accuracy and predictive capability and limited non-destructive measurements, and / or (2) designing geometrical features and parameters of solid materials and structures to achieve optimized and / or improved performance.

The invention discloses a device and method for measuring the abrasion amount of a spray needle of an impulse turbine, and the device comprises a fixed platform which is used for placing the spray needle to be measured, and the spray needle to be measured is provided with a plurality of points to be measured; the inner and outer slide rails are arranged at the top of the fixed platform, are positioned on the outer side of the to-be-measured spray needle and axially coincide with the to-be-measured spray needle; the rotating platform is in sliding connection with the inner and outer sliding rails and can rotate around the to-be-measured spray needle; the telescopic platform is arranged at the top of the rotating platform, and the end, away from the rotating platform, of the telescopic platform is connected with an inclined platform; the distance measuring probe system is detachably connected to the inclined platform, and the measuring end of the distance measuring probe system faces the to-be-measured spray needle; the measuring device is combined with a multi-degree-of-freedom adjusting mechanism to realize accurate positioning and vertical alignment of the probe, then the probe system is used for reading the displacement and deducting the thickness of the sleeve to obtain the real abrasion depth, non-destructive high-precision abrasion amount detection of any point of a complex curved surface can be realized, and the measuring device is suitable for a hydropower station overhaul site.

The invention provides a fatigue test method, system and equipment based on texture change of carbon fibers and a medium, and belongs to the technical field of material tests.The method comprises the steps that a carbon fiber composite material is selected as a test sample; applying a fatigue load to the test sample according to a designed test condition, and collecting a surface image of the test sample; the method comprises the following steps of: preprocessing an acquired image, clustering according to the gray level and texture similarity of pixels to obtain a plurality of clustering subareas, and marking different clustering areas by using different colors to complete color mapping; extracting texture feature parameters from the image after color mapping, and performing PCA dimension reduction to obtain key texture feature parameters; and comparing the key texture feature parameters of the image under different test conditions, identifying texture feature changes, and completing fatigue performance evaluation. According to the method, image processing and texture feature analysis are combined, so that non-destructive testing of the CFRP fatigue performance is realized, and the testing accuracy and efficiency are improved.

The invention discloses a bridge deck pavement layering test method and system based on multi-point knocking and deep learning, belongs to the technical field of bridge engineering, and aims to solve the technical problem of how to efficiently and non-destructively realize bridge deck pavement layering detection and ensure detection precision and construction quality. Comprising the following steps: knocking bridge floor sections through detection equipment provided with a plurality of electromagnetic knocking hammers to obtain sound wave signals in an analog signal form; performing signal amplification, filtering and analog-to-digital conversion processing on the acquired sound wave signal; time domain features and frequency domain features of the sound wave signals are calculated respectively, and a feature matrix is constructed based on the time domain features and the frequency domain features; analyzing the health state of the bridge deck segments through the trained bridge deck pavement layered disease detection model, and predicting and outputting an analysis result; and determining the damaged area of the bridge floor based on the analysis result of each bridge floor segment, constructing a repair suggestion, and constructing a pseudo-color thermodynamic diagram of the bridge floor based on the analysis result of each bridge floor segment.

The utility model discloses a non-destructive agricultural product internal quality measuring device which comprises a light emitting component, a light receiving component, a light guiding component and a heat ray cutting component. The light-receiving member is mounted in a direction perpendicular to the agricultural product transfer direction and is mounted in contrast to the light-emitting member, the light emitted by the light-emitting member is emitted from a light source, and the light transmitted through the agricultural product is received by the light-receiving member, and the light guide member is mounted in front of the light-receiving member side of the light-emitting member. The light guide part is arranged between the light-emitting part and the agricultural product, and a heat ray cutting part is arranged on the light guide part. The utility model belongs to the technical field of non-destructive internal detection of agricultural products, and particularly relates to a device which can be additionally arranged on a standard screening device while maintaining high measurement precision and preventing quality damage of the agricultural products caused by overheating so as to improve the utilization degree.

The invention discloses a chip aging test method based on thermal migration analysis. The method comprises the following steps: acquiring power consumption distribution data, material attribute data and manufacturing process data; discrete mapping and dynamic adjustment are carried out on the power consumption distribution data by adopting finite element network nodes to obtain an initial heat distribution diagram; processing the initial thermal distribution diagram based on a thermal imaging technology to generate a temperature mapping diagram of the surface of the chip; performing network division based on the temperature mapping graph, and generating a heat transfer path graph in combination with a gradient tracking algorithm; based on the heat transfer path diagram, screening a potential area through a preset temperature threshold value, and generating a potential heat distribution diagram through clustering analysis; performing microstructure analysis on the abnormal area according to the potential thermal distribution diagram to generate an abnormal analysis report; and solving high-temperature region distribution according to the manufacturing process data and the anomaly analysis report, and performing region analysis to generate a thermal identification report. According to the method, the problem that the heat transfer path cannot be accurately captured and the hot spot area cannot be identified under the non-destructive test can be solved.

The invention discloses a PCB dielectric layer thickness measurement method, apparatus and device, and a medium. The method comprises the following steps: obtaining a first thickness value of a target dielectric layer measured based on a capacitance test method; wherein the target dielectric layer is a dielectric layer in the PCB to be detected; obtaining a second thickness value of the sample dielectric layer measured based on slice analysis; wherein the sample dielectric layer is a dielectric layer in a sample PCB, and the sample PCB is a PCB which has the same structure as a to-be-detected PCB and is manufactured based on the same process condition; according to the first thickness value and the second thickness value, obtaining a measurement thickness value of the target dielectric layer; wherein the measured thickness value is the average value of the first thickness value and the second thickness value, and the method has the advantages that the measurement precision is improved, and the non-destructive measurement of the to-be-detected PCB can be realized.

The invention discloses a cable terminal crimping quality detection method, device and equipment and a storage medium, and relates to the technical field of cable testing, and the method comprises the steps: exciting a cable terminal through a current pin in the crimping process of the cable terminal, collecting the voltage of the cable terminal through a voltage pin, and obtaining a real-time voltage signal; and evaluating the crimping quality of the cable terminal based on the resistance change condition of the real-time resistance value in the crimping process. According to the invention, the detection behavior and the crimping process are carried out synchronously, and the real-time monitoring of the dynamic change of the resistance in the crimping process is realized, so that the method can be applied to the one-by-one full detection of a production line, and the measurement mode of separating current excitation and voltage collection is adopted. A system error caused by lead resistance introduced by a common lead of current excitation and voltage acquisition is avoided, and real-time performance, non-destructive performance and high precision are effectively considered when the crimping quality of the cable terminal is evaluated.

The invention provides an MLCC short-circuit product defect position analysis method, and belongs to the technical field of multilayer ceramic capacitor failure analysis. The method comprises the following steps: carrying out rapid leakage current detection on MLCC products for 0.5-2 seconds, and screening out short-circuit products of which the leakage current is greater than a first preset threshold value; products with crack defects are eliminated through an acoustic scanning microscope; gradually applying increased direct-current voltage to the screened crack-free short-circuit product, monitoring leakage current in real time, and terminating the test when the sudden change amplitude of the current exceeds a second preset threshold value; then acoustic scanning is carried out on the protective cover surface and the cutting surface, and two-dimensional coordinates of defect points on the two surfaces are extracted; and calculating the three-dimensional coordinates of the defect in the MLCC through image registration and a spatial inversion algorithm. According to the method, the internal hidden short circuit defect can be identified and positioned in a non-destructive manner, the positioning precision and the analysis efficiency are improved, and the method is suitable for batch failure analysis and manufacturing process optimization.

The invention provides a method for monitoring the internal temperature of a single cell of a power battery, and relates to the technical field of battery monitoring, a monitoring method and a cell assembly are included, the cell assembly comprises a cell column, the cell column is wrapped with a cell lamination, the inner side of the cell lamination is provided with a miniature thin film thermocouple sensor, and the miniature thin film thermocouple sensor is arranged in the cell column. Aiming at the problems of insufficient precision, limited environmental adaptability, low intelligent degree and lack of thermal runaway prediction capability in monitoring of the internal temperature of a single cell of a power battery, a micro thin film thermocouple sensor array is embedded, an intelligent data processing flow and a multi-source data fusion design are adopted, and the thermal runaway prediction capability of the single cell of the power battery is improved. And the monitoring precision, reliability and automation level are obviously improved. Firstly, high-precision non-destructive detection and environmental adaptability are realized. The miniature thin film thermocouple sensor array is embedded between the positive and negative plates and the diaphragm, is attached to the non-coating area of the positive plate, and is in direct contact with the active material to construct a three-dimensional distributed temperature monitoring network.

The invention discloses a detection method for fertilizer production, and relates to the technical field of fertilizer detection.The detection method comprises the following steps that a near-infrared multispectral visual detection system is installed at the working section before packaging of a fertilizer production line, the positions of a camera and an illumination source are adjusted, and multispectral images of fertilizer particles are collected; sequentially carrying out dark current correction and flat field correction on the acquired image, eliminating noise and uneven illumination, and then carrying out median filtering to remove random noise; selecting a waveband image with the best contrast ratio, separating particles from the background through threshold segmentation, and positioning each independent particle after optimizing the boundary through morphological processing; and based on the multi-band reflectivity difference, analyzing the surface material of the particles pixel by pixel, and counting the proportion of the coating area of each particle to obtain the coating coverage rate of the single particle. By introducing the near-infrared multispectral visual detection technology and the coating uniformity quantitative analysis model, non-destructive and high-precision online detection of the coating coverage rate of the fertilizer can be realized.

The invention belongs to the technical field of image processing, and particularly relates to an inonotus obliquus raw material granularity and uniformity detection method based on image analysis, and the method comprises the steps: obtaining an inonotus obliquus raw material gray scale image, and carrying out the preprocessing and binaryzation to obtain an adhesion body candidate object; screening particle core seed points through distance transformation in combination with an adaptive threshold strategy based on image statistical characteristics; calculating the attribution probability of a pixel to a seed point through a geodesic distance, achieving the soft segmentation of an adhesion region through a negative index model, and extracting a non-destructive segmentation line to obtain independent particles; and calculating morphological parameters of the particles, and obtaining a global uniformity index by combining the size dispersion and the shape regularity. According to the method, the accuracy of adhesion segmentation of irregular inonotus obliquus raw materials with complex textures is improved, and the robustness and accuracy of granularity detection are improved.

A system for non-destructive characterization of specimens that includes an electron beam (e-beam) source for projecting e-beams at one or more e-beam landing energies on a specimen; an X-ray detector for sensing X-rays emitted from the specimen, thereby obtaining measurement data; and processing circuitry configured to: (i) extract from the measurement data key features specified by a vector {right arrow over (f)}key; and (ii) estimate values {right arrow over (p)} of one or more structural parameters, characterizing the specimen, based on {right arrow over (f)}key and a set of vectors of ground truth (GT) and simulated key features {{right arrow over (f)}n}n=1N. Each of the {right arrow over (f)}n is a product of GT measurements or of computer simulations of emission of X-rays from a respective GT or simulated specimen due to impinging thereof with e-beams at each of the one or more landing energies.

The invention relates to the technical field of information, in particular to a black land plough layer thickness analysis method based on machine learning. The scheme has the advantages that double-frequency radar signals (200MHz low frequency and 2GHz high frequency) are combined with power amplification and a broadband antenna, a double-layer feature comparison model is constructed by utilizing the frequency sensitivity inversion characteristic of dielectric constant difference between a plough layer and a plough pan, interface details are captured in cooperation with a 1GS / s super-Nyquist sampling rate, a strong regression model is constructed in combination with an AdaBoost algorithm, and a high-precision feature comparison model is constructed. The method achieves the high-precision, non-destructive and large-area rapid detection of the thickness of the plough layer of the black land, and solves the problems that a conventional method is time-consuming and labor-consuming, is low in precision, and cannot give consideration to the penetration depth and resolution of a single-frequency radar.

The invention discloses a semiconductor device packaging thermal resistance test method and system, and the method comprises the steps: applying multi-point pulse current excitation to a package, collecting surface temperature response data, and constructing a three-dimensional heat conduction path structure of the package; based on the structure, initial thermal resistance distribution and a non-uniform region thereof are calculated, and thermal resistance separation parameters at each hierarchical interface are further extracted to form a hierarchical thermal resistance separation matrix. Directional correction is carried out on the thermal resistance value containing the anisotropic heat conduction material, a corrected hierarchical thermal resistance sequence is generated and superposed with the initial thermal resistance distribution, and finally the total thermal resistance value of packaging is calculated. The accuracy of hierarchical thermal resistance separation is ensured by verifying the matching degree of the total thermal resistance value and the temperature response data, and a detailed thermal resistance distribution map is output, so that the thermal resistance contribution of each hierarchy in the package can be non-destructively and accurately separated and quantified, and particularly, when facing non-uniform heat flow distribution and anisotropic heat-conducting materials, the thermal resistance contribution of each hierarchy in the package can be accurately separated and quantified. And the accuracy of a measurement result is improved through directional correction.

The invention aims to provide the system and the method for precisely measuring the heat conduction performance of the vapor chamber, which can eliminate errors caused by contact thermal resistance by utilizing the vapor chamber, and is high in spatial resolution and non-destructive in test. The uniform temperature plate heat conduction performance precision measurement system comprises a temperature measurement module, the temperature measurement module comprises a heating module and a plurality of measurement modules, each measurement module comprises a thermocouple probe and a force adjusting mechanism which are connected, and each thermocouple probe comprises a T-shaped thermocouple, a positive electrode temperature measurement pressure head and a negative electrode temperature measurement pressure head. The positive temperature measuring pressure head and the negative temperature measuring pressure head are mutually independent and are arranged in a floating mode relative to the force adjusting mechanism, the positive temperature measuring pressure head is provided with a copper thermocouple wire connected to the positive electrode of the T-type thermocouple, and the negative temperature measuring pressure head is provided with a constantan thermocouple wire connected to the negative electrode of the T-type thermocouple. The copper thermocouple wire and the constantan thermocouple wire are short-circuited and form a thermocouple loop when being in contact with the vapor chamber at the same time; the method is realized based on the measurement system. The method is applied to the technical field of vapor chamber testing.

The invention discloses a real-time monitoring method for local corrosion of a copper base material based on a discrete FBG sensor, and belongs to the technical field of metal corrosion monitoring. FBG strain sensors and temperature compensation sensors are distributed on the surface of the copper base material, and a temperature compensation mechanism is matched to eliminate measurement errors caused by environment temperature changes, so that the real-time monitoring of local corrosion of the copper base material is realized. Bragg wavelength drift caused by corrosion product accumulation in the corrosion process is collected in real time, and then real-time and continuous tracking of the corrosion dynamic process is obtained. The method realizes early recognition, accurate positioning and quantitative evaluation of local corrosion of the copper base material, has the advantages of non-destructiveness, high sensitivity, long-term stability and the like, and is suitable for corrosion health monitoring of copper structures such as ocean engineering, buildings, pipelines and the like.

The utility model discloses a leak detection device in an automobile evaporator core body, and relates to the technical field of automobile cooling systems. The device comprises a detection platform and an ultrasonic detection system, and two detection stations are arranged on the detection platform and used for placing evaporator cores; each detection station is provided with a connecting block which is used for being connected with an interface of an evaporator core body. The ultrasonic detection system is connected with the two connecting blocks through a channel switching mechanism at the same time, and the ultrasonic detection system is only communicated with the evaporator core of one detection station through switching. In the detection process, ultrasonic waves are transmitted through the interior of the evaporator core and return to the detection system, and therefore inner leakage detection is achieved. The device adopts a double-station design and an automatic channel switching mechanism, so that the detection efficiency and accuracy are remarkably improved, the manual intervention is reduced, and the device has the characteristics of low cost, non-contact property and non-destructive property. The method is suitable for batch detection of evaporators of different specifications, and can be widely applied to evaporator inner leakage detection of an automobile air-conditioning system.

The invention provides a carbon fiber three-dimensional density measurement method and system, and relates to the technical field of material detection. Comprising the following steps: irradiating a to-be-detected sample with X-rays, and collecting a plurality of interference images formed after the X-rays penetrate through the to-be-detected sample at different angles of the to-be-detected sample; calculating two-dimensional density distribution of the to-be-detected sample at each angle according to the interference image; and carrying out tomographic reconstruction on the two-dimensional density distribution at the plurality of angles to obtain a three-dimensional density distribution image of the sample to be detected. According to the carbon fiber three-dimensional density measurement method, a multi-angle X-ray interference image is collected, and the density change of the carbon fiber reinforced composite material is reflected by using phase information, so that the density resolution of the carbon fiber reinforced composite material is improved; the method is non-destructive, and is suitable for efficient and reliable analysis of the internal structure of a complex material.

The invention provides a hard and brittle material subsurface damage mechanism signal classification method based on an acoustic emission technology. The method comprises the following steps: firstly, acquiring an acoustic emission original signal and surface appearance of the hard and brittle material through grinding tests at various grinding speeds; then, carrying out preprocessing and time-frequency domain feature extraction on the acoustic emission signals by using a wavelet packet signal processing algorithm and short-time Fourier transform; finally, distinguishing a micro-crack signal, a radial crack signal and a transverse crack signal from the characteristic space by combining the damage characteristics and acoustic emission characteristic parameters of the hard and brittle material, and obtaining a characteristic frequency band range corresponding to each crack damage mode; a hard and brittle material subsurface damage mechanism signal classification model is constructed, and a theoretical basis is provided for monitoring of grinding subsurface damage of hard and brittle materials under complex working conditions. According to the method, the damage mechanism of the hard and brittle material can be quickly identified, the subsequent online evaluation of the subsurface damage of the hard and brittle material is realized, and the technical problem of non-destructive accurate monitoring in the grinding process is solved.

The invention belongs to the technical field of prefabricated part mounting systems, and particularly relates to a quick mounting and accurate positioning system for prefabricated parts of an assembled house, comprising a prefabricated part transportation module for transporting the prefabricated parts from a production site to a construction site; according to the invention, through a millimeter-level high-precision positioning reference point of the positioning reference module, an accurate space coordinate reference is provided for component installation; the component posture adjusting module has a fine adjustment function, the fine adjustment precision reaches + / -0.1 mm, and the component posture can be finely adjusted; the precise positioning control module adopts a hybrid algorithm based on fuzzy control and neural network control, parameters can be automatically adjusted according to different installation environments and component types, and positioning precision and stability are improved. Meanwhile, the quality detection module is combined with a non-destructive detection technology and an image recognition technology, the installed component is comprehensively detected, internal defects can be accurately recognized and marked, and strength detection is conducted on the connecting part to ensure firm connection.

The invention provides a phase classification method for coal combustion fly ash, and relates to the technical field of coal combustion byproduct analysis. The phase classification method comprises the following steps: performing consolidation treatment on a coal combustion fly ash sample to obtain a to-be-analyzed target sample; carrying out element component collection on the plurality of particle micro-areas in the to-be-analyzed target sample based on scanning electron microscope energy spectrum analysis to obtain the contents of main control elements and target elements; and according to the contents of the main control element and the target element, performing phase classification on the plurality of particles contained in the coal combustion fly ash sample, and determining the phase category to which each particle belongs. According to the method, through consolidation sample preparation and scanning electron microscope energy spectrum analysis, non-destructive and multi-element micro-area analysis of the fly ash particles is achieved, phase classification is completed based on the element content, and the classification accuracy and the research foundation are improved.

The invention discloses a friction welding bead offset detection method, friction welding equipment and a workpiece. The friction welding bead offset detection method comprises the steps that a target workpiece is placed on an XY moving platform, and the target workpiece is provided with a first detection symbol and a second detection symbol; the XY moving platform, the Z-axis mechanism and the C-axis mechanism are used for controlling a stirring needle to conduct friction stir welding on the target workpiece, so that a friction welding bead is formed on the target workpiece; controlling the stirring needle to perform primary dotting on the first detection symbol so as to form a first detection point on the target workpiece; the stirring needle is controlled to perform secondary dotting on the second detection symbol so as to form a second detection point on the target workpiece, and the difference value of the C angle parameter of the C-axis mechanism between the primary dotting and the secondary dotting is 180 degrees; and according to the first detection symbol, the first detection point, the second detection symbol and the second detection symbol, friction welding bead offset detection is conducted, and an offset detection result is obtained. According to the invention, offset detection can be carried out on the friction welding bead in a non-destructive manner.

The invention discloses a method for realizing TSV failure verification of a 3D chip product, and the method comprises the steps: enabling the upper end of a TSV group to be connected to an upper chip in a 3D chip, enabling the lower end of the TSV group to be connected to a bottom chip in the 3D chip, and screening and positioning a suspected TSV structure in the TSV group through a chip testing technology; grinding the upper chip and the bottom chip to expose the metal layers at the top and the bottom of each TSV structure, and establishing electrical interconnection of each TSV structure on the bottom metal layer; and based on the electrical interconnection of the metal layers, performing an electrical test on the suspected TSV structure and the contrast TSV structure in the TSV group, and determining whether the suspected TSV structure is abnormal or not according to comparison information of an electrical test result. According to the scheme of the invention, non-destructive TSV electrical testing is realized.