683 results about "Non destructive" patented technology

The present invention relates to the field of road engineering technology, and specifically to a non-destructive detection method and system for internal defects and compactness of concrete, the method comprising: collecting dynamic response data of the internal structure of concrete, and preliminarily determining the stress abnormality area; according to the preliminarily determined stress abnormality area, deploying an intelligent sensor array, monitoring the physical state data of the local area, and generating depth monitoring data; synchronously emitting sound waves and vibration waves in the local area, monitoring the propagation path and phase change, and obtaining propagation characteristic data; reconstructing the distribution state of concrete density, and simulating the dynamic response under different load conditions to obtain compactness detection results. Through the present invention, the problems of destructive sampling, local detection and insufficient precision existing in traditional methods are effectively solved, and high-precision and comprehensive detection of internal defects of concrete is achieved, thereby improving the safety and reliability of concrete structures.

The invention discloses a method for analyzing mineral trace elements by utilizing a micro-Raman spectrum, which comprises the following steps of: fixing a mineral sample on a rotary sample table of a micro-Raman spectrometer, selecting an area to be detected by combining a micro-imaging technology, collecting a Raman background signal under the pre-illumination of low-power laser, and analyzing the trace elements in the area to be detected according to the Raman background signal. The laser focal length, the spot size and the incident angle are adjusted accordingly, the laser is focused on a target area, under the calibrated laser condition, through a multi-angle excitation micro-area, after an algorithm is applied to optimize signals, reduce impurity interference and integrate multi-angle Raman signals, the characteristic spectrum information of the microelements can be extracted, and the microelements can be accurately detected. High-resolution analysis of sample components is realized, and a three-dimensional distribution model of microelements in a microcell is constructed in combination with microscopic imaging data. The method has the characteristics of non-destructiveness, high resolution and rapid detection, and is suitable for mineral component analysis in the fields of geology, material science and the like.

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 present disclosure discloses a non-destructive detection method and system for Conopomorpha sinensis Bradley, which includes: placing a lychee sample to be detected on a conveyor belt; acquiring sample information of the lychee sample based on visible / near-infrared light and X-ray imaging technology; wherein the visible / near-infrared light acquires internal quality features of the lychee sample; the X-ray imaging technology acquires internal density variation features of the lychee sample; analyzing the sample information according to a preset data processing and analysis method based on PLSR and a support vector machine to obtain a classification result of the lychee sample. The present disclosure uses the visible / near-infrared transmission spectrum and the X-ray imaging feature fusion in combination with PLSR to improve the detection accuracy of the lychee sample of the testing set to 92.92%, and in combination with the support vector regression to obtain a classification accuracy of 94.44% of the testing set.

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 an ultrasonic nondestructive testing method for residual stress of a titanium alloy pipe, and relates to the technical field of metal detection. Comprising the following steps: carrying out surface residual stress benchmark measurement, selecting an ultrasonic emission frequency, carrying out pretreatment on the surface of the titanium alloy pipe, carrying out multi-mode ultrasonic beam focusing scanning, establishing an ultrasonic speed and stress correlation model, carrying out acoustic anomaly identification on an asymmetric stress area, carrying out residual stress three-dimensional imaging, and correcting stress distribution. According to the ultrasonic nondestructive testing method for the residual stress of the titanium alloy pipe, by combining ultrasonic signal processing, complex stress correlation modeling and acoustic anomaly recognition technologies, the defects of a traditional testing method in the aspects of precision, adaptability and non-destructiveness are overcome. The distribution and concentration condition of the residual stress of the titanium alloy pipe can be efficiently and accurately evaluated, and the reliability and environmental adaptability of a detection result are effectively improved.

The present invention relates to a solution for non-destructive quantification of one or more chemical substances in a matrix comprising coating and bulk material in a sample, for example coated seeds, using Infrared Spectroscopy data of the sample and a computer-implemented multivariate data analysis

The invention discloses a hyperspectral prediction method and device for the soluble solid content of winter jujubes and a storage medium, and belongs to the field of material testing and analys.The method comprises the steps that firstly, a winter jujube sample is obtained, and spectral data and soluble solid content data of the winter jujube sample are measured; preprocessing the spectral data by using a preset data preprocessing method to obtain enhanced spectral data, constructing an input sample set through the obtained enhanced spectral data, and constructing an output sample set through the measured soluble solid content data; then, the input sample set and the output sample set are used for training a pre-configured LSTM-Transformer network, and the pre-configured LSTM-Transformer network is used for training the pre-configured LSTM-Transformer network; and finally, deploying the trained LSTM-Transform network as a winter jujube SSC hyperspectral prediction model so as to predict the soluble solid content of the winter jujube. Through the steps, the soluble solid content of the winter jujube sample can be quickly and non-destructively predicted with high precision, so that the consistency and the stability of the product quality are ensured.

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 invention discloses a corrugated carton forming detection device in the field of quality detection equipment. The corrugated carton forming detection device comprises a conveying platform; a main conveying belt and a detection part are arranged on the conveying platform; a supporting assembly, a plurality of attaching assemblies, a vibration assembly, an acquisition module and a control module are arranged in the detection part; the supporting assembly is used for supporting the side wall of the corrugated carton from the interior of the corrugated carton based on the air pressure expansion principle. The laminating assembly is used for laminating and fixing the surface of the corrugated carton to be tested; the vibration assembly is used for enabling the corrugated carton to be tested to generate vibration; the acquisition module is used for acquiring the air pressure change condition of the supporting assembly in the detection process; the control module is used for controlling operation of the attaching assembly, the supporting assembly and the vibration assembly and judging the quality of the corrugated carton based on the air pressure change condition of the supporting assembly. According to the scheme, through non-destructive air pressure expansion and vibration testing, direct physical damage to the carton is avoided, and therefore the recycling rate of the carton is increased.

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 provides a performance resistance monitoring system and method of a load environment coupling loading CFRP part, and relates to the technical field of carbon fiber composite materials. The system comprises a stress loading regulation and control assembly, a water circulation assembly, a radial resistance detection assembly and a transverse resistance monitoring assembly, and aims to realize dynamic monitoring of the conductivity, the water absorption rate and the damage process of the material by monitoring the resistance change rule of the CFRP in real time. The system comprises a stress loading regulation and control assembly, a radial resistance monitoring assembly, a water circulation assembly and a transverse resistance monitoring assembly. Through long-term resistance monitoring, analysis of the corresponding relation between the mechanical property and the resistance, establishment of an empirical model formula and estimation of the degradation degree of the mechanical property, the invention provides an efficient and non-destructive evaluation means; the method is used for predicting the service life of the CFRP and guiding maintenance and replacement strategies. According to the method, real-time dynamic monitoring of the conductivity, the water absorption rate and the damage process of the CFRP under the force-salt-heat-humidity multi-factor coupling effect is achieved.

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 relates to a method for disassembling a main drive of a double-shield TBM (tunnel boring machine) in a tunnel, which belongs to the field of disassembly and assembly and comprises the following steps: (1) preparation work; (2) cutting an anterior shield; (3) lifting lugs are welded, and lifting points are arranged; (4) disassembling and turning over by a main driving method; and (5) transporting a main drive. The in-hole dismounting key technology for the double-shield TBM main drive has the advantages that the problem of non-destructive dismounting of the main drive in a narrow space of an equipment shield body is well solved, secondary use of core components is guaranteed, the recovery cost after in-hole shell abandoning and machine dismounting is greatly saved, and the in-hole dismounting key technology is safe, economical and feasible and has wide application prospects. And the method can be used for subsequent dismounting construction of the main drive in similar in-hole shell abandoning and dismounting machines.

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 relates to the technical field of cynomorium songaricum identification, in particular to a method for rapidly identifying cynomorium songaricum of different processing modes and host plants based on an electronic tongue technology. The method comprises the following steps: weighing 1.0 g of a sample, adding 10mL of water, dissolving, filtering after 30min, repeating for three times, merging filtrate, obtaining a test solution, and detecting by using an electronic tongue; statistical analysis; the method has the beneficial effects or advantages of rapid and accurate quality identification, non-destructive detection, diversified processing modes and host plant identification, promotion of healthy development of the cynomorium songaricum industry, improvement of intelligent and automatic levels and the like. Due to the advantages, the method has wide application prospects and market potential in the field of cynomorium songaricum quality identification.

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.