43results about How to "Accurate mass" patented technology

The invention discloses an image super-resolution reconstruction method based on compressed sensing, and belongs to the field of image reconstruction. The problems that the updating speed of existing hardware cannot meet the requirement for signal precision, and on the premise that the hardware cost is not increased, an image with higher definition cannot be reconstructed are solved. The invention discloses an image super-resolution reconstruction method based on compressed sensing, and the method comprises the steps: designing a dictionary learning process, and obtaining high-frequency component parameters needed in image restoration; comprising the steps of constructing a training data set and performing dictionary training; wherein a corresponding low-resolution image is obtained by carrying out quality reduction and scale reduction calculation on an image so as to carry out a process of training a data set; constructing an over-complete dictionary pair by using a K-SVD algorithm, and training the dictionary; firstly, a reduced low-frequency component is obtained, and then the resolution is reconstructed. According to the method, the GPSR algorithm is utilized, the limitation of fixed sparseness of a traditional OMP algorithm is overcome, a more accurate sparse coefficient is obtained, and the precision of the reconstructed image is further improved by adopting a bilateral filtering mode.

The invention relates to the technical field of image recognition, in particular to a quality detection and recognition method. The method comprises the steps of performing spatial mapping on an original image, performing feature extraction on the mapped image, performing step-by-step segmentation on an obtained image to be layered, extracting a required layer, forming color features by using color information of the layer, performing regression judgment through machine learning training, and obtaining a score. The color features are calculated through distribution of hue, saturation and brightness of each pixel in the image and comprise one or more combinations of a mean value, a standard deviation and a deviation. Through computer vision and image processing technologies, an optimal detection area in a sample is automatically identified and analyzed, stratified analysis is carried out, multi-dimensional quality data of the sample is detected, and rapid and accurate acquisition and quality evaluation of the multi-dimensional quality data of the sample are realized. For the evaluation standard difference of different groups, only the evaluation score Y value needs to be adjusted, the model does not need to be trained again, and the application range of the method is greatly widened.

The invention provides a mold plate quality detection method and system based on machine vision, and the method comprises the steps: obtaining a template image and a to-be-detected plate image through the shooting of a camera, and obtaining an image frame through an optical flow method; the method comprises the following steps: preprocessing an image, and extracting an edge through Canny edge detection; matching the feature points by using an RANSAC (Random Sample Consensus) algorithm, and removing mismatched point pairs; obtaining a feature line segment; matching the feature line segments by using an SURF algorithm, and calculating a matching line segment ratio; oRB feature point matching is carried out; carrying out line lofting registration; calculating comprehensive plate quality information; and obtaining a quality inspection result according to the quality information. According to the invention, efficient and accurate detection of the quality of the mold plate can be realized, and the automation level and accuracy of detection are improved.

The invention discloses a size measurement control method for steel billet forging, and belongs to the technical field of industrial visual intelligence. The method comprises the following steps: acquiring material information, three-dimensional point cloud and temperature information of a target steel billet; based on the three-dimensional point cloud, performing three-dimensional modeling on the target steel billet to determine size information of the target steel billet; under the condition that it is determined that the temperature information meets the forging condition, the to-be-machined position of the target steel billet is determined according to the size information; the material information and the temperature information corresponding to the to-be-machined position are input into a machining prediction model, the forging force, corresponding to the to-be-machined position, output by the machining prediction model is obtained, and the machining prediction model is obtained based on a data set comprising a plurality of training samples; and based on the to-be-machined position and the forging force, parameter configuration is conducted on the forging machine, so that the forging machine is controlled to forge the to-be-machined position of the target steel billet with the forging force. The method improves the forging precision and the forging effect of the steel billet.

The invention discloses welding equipment for part machining, and relates to the technical field of mechanical part welding, the welding equipment comprises a machining table and further comprises a clamping device, a placing frame is fixedly mounted at the top of the machining table, a placing hole is formed in the top of the placing frame, a welding device is arranged in the placing hole, a supporting groove is formed in the top of the machining table, and a clamping device is arranged in the supporting groove. A supporting rod is fixedly installed on the inner wall of the supporting groove, a displacement device is slidably installed on the circumferential face of the supporting rod, a supporting frame is fixedly installed on the top of the machining table, a supporting plate is fixedly installed on the surface of the displacement device, and the two cambered surface plates move oppositely to make contact with the inner wall of the tubular workpiece and extrude and fix the inner wall of the tubular workpiece. The inner wall of the tubular workpiece is fixed, so that the stability of the position of the tubular workpiece in the welding process can be ensured, and the problem of weld joint deviation or non-uniform quality caused by the unstable position of the tubular workpiece in the welding process can be solved.

The invention relates to the field of building material detection, in particular to a quality evaluation method based on low-water-binder-ratio concrete, which comprises the following steps: acquiring a low-water-binder-ratio concrete sample, confirming a sample detection environment based on the low-water-binder-ratio concrete sample, performing cutting operation on the low-water-binder-ratio concrete sample by using a table-type cutting machine, and determining the quality of the low-water-binder-ratio concrete sample. Calculating an intensity value by using a drying tester and a burning tester; calculating a penetration value by using a penetration controller and a penetration tester; starting an ultrasonic sensor; calculating a loss value by using a sending voltage and a receiving voltage; and constructing a concrete quality evaluation model based on a regression analysis result, substituting the strength value, the permeation value and the hydration value into the concrete quality evaluation model to calculate an evaluation value, and completing quality evaluation of the concrete with the low water-binder ratio. According to the invention, the detection speed and accuracy of the low-water-binder-ratio concrete can be improved.

The present invention provides a method, system and equipment for monitoring the quality of trenching operations based on rapeseed planting, and relates to the technical field of agricultural engineering. The present invention cleans and standardizes the collected data, calculates the characteristic value deviation and generates a characteristic vector, and then establishes a quality evaluation model through a neural network convolution structure to output a trench quality index. The evaluation index is calculated in combination with the temperature and humidity data of the actual environment, and the threshold is dynamically corrected to form a correction value. By comparing the trench quality index and the correction value, it is determined whether the trench meets the trenching quality standard. The present invention realizes dynamic matching and optimization of the trench quality standard and the rapeseed planting demand by collecting and processing the trench characteristic data after the trenching machine operation and combining the relevant parameters of the trench after trenching.

The invention belongs to the technical field of point cloud data processing, and particularly relates to a cross-platform laser point cloud data registration quality evaluation method, which comprises the following steps: for registered cross-platform laser point clouds, extracting spatial geometric features of points, straight lines and planes from laser point clouds obtained by platforms; constructing a cross-platform laser point registration quality evaluation index based on spatial point features, a cross-platform laser point registration quality evaluation index based on spatial straight line features and a cross-platform laser point registration quality evaluation index based on spatial plane features, and combining to form a cross-platform laser point cloud registration quality evaluation index based on spatial features; and performing cross-platform laser point cloud registration quality comprehensive measurement evaluation on the registered cross-platform laser point cloud by using the cross-platform laser point cloud registration quality evaluation index based on the spatial characteristics. According to the method, the registration quality of the multi-source point cloud data can be evaluated more comprehensively and accurately.

The application discloses a kind of for the method, device, equipment and medium of tab abnormality detection in battery cell production process, comprising: the tab area image collected in battery cell production process is segmented to generate tab mask;Based on the tab mask extraction multi-scale pixel-level feature vector, and the multi-scale pixel-level feature vector is input into unsupervised probability GMM model to identify pixel-level abnormal point;The pixel-level abnormal point is analyzed to obtain candidate abnormal area, and the parameter index of the candidate abnormal area is obtained;Determine whether the parameter index meets the set tab abnormality judgment rule, if meet, it is judged as tab abnormality, and tab abnormality result is output.Therefore, the application can be widely applied to the detection of tab folding, crease, fracture, misplacement and other abnormalities on battery cell production line.

The invention provides a light field image quality evaluation method based on a visual language model. According to the method, multi-dimensional comprehensive evaluation of a light field image is realized through the following steps of: (a) evaluating the definition, brightness, angle consistency and the like of the light field image through antonym prompt pairing by utilizing a text prompt function of a visual language model; (b) removing fixed position embedding of a visual language model image encoder so as to improve the adaptability of the model to light field images with different space and angle resolutions; (c) finely adjusting the antonym prompt pair by using a context optimization technology to adapt to the multi-view characteristic of the light field image, and keeping the network weight of the visual language model unchanged; and (d) comprehensively evaluating the light field image based on multi-dimensional evaluation indexes such as brightness, color and angle consistency, and generating an overall quality score. The method can be used for efficient coding, transmission, rendering and other light field image processing scenes, and a new solution is provided for light field image quality evaluation.

The utility model relates to the technical field of automobile lighting manufacturing, and discloses an automobile projection lamp image inspection device which comprises a photographing bottom plate and further comprises two symmetrical supporting plates arranged at the top of the photographing bottom plate, a top plate is arranged between the two symmetrical supporting plates, and a photographing lamp positioning block is arranged at the top of the top plate. A photography lamp body is arranged at the bottom of the photography lamp positioning block; according to the utility model, through the arrangement of the adjusting mechanism, the detection efficiency and accuracy are improved, the labor cost is reduced, the standardized detection is realized, the processing and analysis of a large amount of data can be quickly and accurately completed, and high-precision optical instruments and algorithms are adopted; according to the method, the quality problem of the atmosphere lamp can be identified and judged more accurately, the detection accuracy and reliability are improved, the standardized detection process and algorithm are adopted, the stability and consistency of the detection result are ensured, and the influence of human factors on the detection result is avoided.

The present invention discloses an intelligent grouting station for underground coal mines, comprising a mine explosion-proof control cabinet, a dry powder spiral conveying system, a pulping system, a slurry storage system and a grouting system. The mine explosion-proof control cabinet, the dry powder spiral conveying system, the pulping system, the slurry storage system and the grouting system are arranged in a straight line. The dry powder spiral conveying system is connected to the pulping system and conveys dry powder to the pulping system. The pulping system is connected to the slurry storage system and conveys finished slurry to the slurry storage system. The grouting system is connected to the slurry storage system and sucks out the slurry and injects it into the working surface. The dry powder spiral conveying system, the pulping system, the slurry storage system and the grouting system are all electrically connected to the mine explosion-proof control cabinet. The present invention has a high degree of automation by setting an intelligent measurement system and an electric control system, and the slurry is accurately proportioned, the slurry is of better quality, the preparation speed is fast, the manual operation is reduced, the labor intensity of the staff is reduced, and the work efficiency is improved; the modular design of the whole machine is more convenient for assembly and transportation in a narrow environment.

The invention discloses a transplanting microenvironment construction device and an application method thereof, and aims to improve the seedling standing rate and the qualified rate of rape blanket seedling crops. According to the device, the land preparation device is innovatively designed, ridge surface micro ridges are formed, ridge planting of the planting device is facilitated, and the crop seedling rate and the qualified rate are increased. The device has the soil crushing and growth gathering functions, soil softening and ventilation are facilitated, and a good environment is provided for crop growth. The planting device can accurately control the planting depth and the planting angle, and the stability and the consistency of the growth environment in the seedling stage are ensured. The application method is simple and easy to implement, can be widely applied to agricultural production, and has important significance on improving the production efficiency and quality of crops such as oilseed rape.

The invention discloses a concrete structure strain monitoring device which comprises a shell, a partition plate, a strain sensor and a sensor connecting piece. The partition plate is arranged in the shell and divides the shell into a first cavity and a second cavity; the sensor connecting piece and the strain sensor are arranged in the first cavity, and the second cavity is used for pouring concrete. When concrete is poured, the monitoring device is buried in the concrete, and the concrete in the second cavity pushes the partition plate to move when strain occurs, so that the strain sensor is compressed and strain data is measured. The monitoring device can ensure that concrete inside and outside the shell has the same physical characteristics and maintenance conditions, and the concrete in the shell can freely stretch out and draw back. And moreover, the data processor is used for acquiring concrete strains epsilon inside and outside inside and outside the detection device, so that the stress-related strain epsilon stress correlation of the concrete structure can be calculated, the interference of non-stress strain is reduced, and the concrete quality and safety evaluation is more accurate.

The invention relates to the technical field of thermoelectric Internet of Things safety, in particular to a heat meter verification data intelligent analysis system based on heat supply multi-parameter simulation, which comprises a multi-parameter working condition simulation module, a data acquisition and communication module, a verified household heat meter, a data processing and storage module, an intelligent analysis core module and a calibration optimization suggestion module, the multi-parameter working condition simulation module accurately reproduces water quality, temperature, flow velocity and battery electric quantity coupling working conditions; the data acquisition and communication module realizes unified acquisition of heat meter data of multiple brands; the intelligent analysis core module quantifies working condition coupling influence, sorts heat table performance and predicts the service life of the battery through a multivariate regression + SHAP hybrid model, an entropy weight-TOPSIS method and an ARIMA model; the calibration optimization suggestion module generates a dynamic calibration coefficient. According to the invention, all-condition verification, intelligent analysis and accurate optimization of the heat meter are realized, data support is provided for purchase, calibration, operation and maintenance of the heat meter of a heat supply enterprise, and the metering accuracy and the energy utilization efficiency are improved.

The utility model provides an automatic tea picking machine which comprises a picking action mechanism, the picking action mechanism comprises a shell and a bionic mouth clamp arranged on the front side of the shell, the bionic mouth clamp is composed of an upper clamp body and a lower clamp body which are vertically symmetrical, the upper clamp body and the lower clamp body are rotationally connected with the front side of the shell respectively, and an upper blade and a lower blade are arranged on the front sides of the opposite sides of the upper clamp body and the lower clamp body respectively. When the bionic mouth clamp is closed, the upper blade and the lower blade perform cutting action; the picking driving mechanism is arranged in the shell and used for driving the bionic mouth clamp to be closed or opened; the collecting mechanism comprises a backpack, a suction mechanism is arranged in the backpack, the backpack is communicated with the interior of the shell through a pipeline, and when the bionic mouth clamp is closed, a cavity formed in the bionic mouth clamp is communicated with the interior of the shell. The tea leaf picking machine is light and easy to operate, the backpack and the suction mechanism can automatically collect tea leaves, physical labor is relieved, the duckbilled scissors complete the pruning and temporary storage process, the size of the duckbilled scissors is suitable for the tea leaves with the average size, and the accurate picking precision and quality are guaranteed.

The application provides a tunnel lining concrete evaluation method and system, and belongs to the technical field of tunnel lining quality detection. The method comprises the following steps: a data acquisition and matrix construction step: obtaining full polarization data and establishing a complex domain scattering matrix of each sampling point; a spatial phase locking step: constructing a spatial phase locking loop, tracking the spatial phase of the steel bar in real time, determining the locking state according to the phase difference and determining the steel bar high-weight prediction area; a polarization feature calculation step: in the steel bar high-weight prediction area, performing eigenvalue decomposition on the local covariance matrix, calculating the polarization entropy and the average scattering angle; an adaptive projection stripping step: generating an adaptive gain factor and adjusting the projection strength of the projection matrix, performing projection transformation on the original polarization vector to obtain a residual signal; and an evaluation step: reconstructing a defect signal based on the residual signal to evaluate the quality of the tunnel concrete lining. The scheme can improve the accuracy of tunnel concrete lining quality evaluation.

The invention provides a plug-in adjustable planting distance dibbler which comprises a mounting frame, the mounting frame comprises a left mounting base frame and a right mounting base frame, the left end and the right end of a movable adjusting frame are slidably arranged in first sliding grooves of the two mounting base frames respectively, and hole forming assemblies are arranged at the left end and the right end of the movable adjusting frame respectively. Each group of hole forming assembly comprises a seed taking device, a telescopic sleeve and a hole forming device, the seed taking device comprises a seed box and a seed guide pipe, the seed guide pipe is fixed on the movable adjusting frame, the telescopic sleeve is sleeved on the seed guide pipe in a sliding manner, and the hole forming device is arranged at the bottom of the telescopic sleeve; a driving mechanism and an adjusting mechanism are arranged on the mounting frame, and the driving mechanism drives the movable adjusting frame and the left two sets of hole forming assemblies to move front and back together; the adjusting mechanism is matched with the driving mechanism to drive the telescopic sleeves in the two groups of hole forming assemblies to slide up and down so as to perform hole forming and seeding operation. The seeder has the advantages that zero-speed automatic hole forming and seeding of the seeder are realized, and meanwhile, the seeding plant spacing can be flexibly and effectively adjusted.

The invention discloses a thread rolling machine limiting support plate suitable for short thread positioning, which comprises a raised head (1), a body (2) and a tail part (3). The convex head (1) and the tail part (3) which are integrated are respectively arranged at two ends of the body (2). The short thread type product positioning device is accurate in positioning of short thread type products, avoids the situation that threads go onto a platform and polish rods are scratched due to positioning deviation in the product machining process, and guarantees the product quality.

The invention discloses a 3D printer remote control method and system based on an image tracking technology, and the method comprises the steps: determining a difference part image of a first image printed at a current moment and a second image printed at a previous moment through the image tracking technology; according to the difference part image, whether the printing quality score is smaller than or equal to the printing quality score standard value is determined, a new method for determining the printing quality score is provided, in addition, direct comparison is conducted by combining front and back collected frame images, and therefore the printing quality is measured through the difference degree. In this way, the data of the next frame can be checked in time through the data of the previous frame, so that on one hand, the speed is higher, and on the other hand, quality determination is more accurate based on printing continuity of printed products.

The invention discloses a Mini LED backlight function test method and system based on optical detection. Comprising the following steps of: controlling an industrial camera CMOS (Complementary Metal Oxide Semiconductor Transistor) to shoot a high-resolution gray-scale image of a Mini LED backlight lamp bead in an experimental environment; the method comprises the following steps: marking a shot and captured backlight bead target in an input grayscale image through a connected region marking algorithm, extracting feature information such as a target pixel position, an external rectangle size and an average grayscale, and obtaining average brightness feature information; according to the target set extracted by marking and the target feature information, combining abnormal judgment threshold processing judgment, and extracting a target with abnormal brightness; carrying out positioning output on the abnormal Mini LED lamp bead target by adopting a target self-adaptive positioning algorithm; and adopting a double-label detection correction algorithm based on a pixel space and a target object to detect the LED Open / Sport and carry out positioning output. According to the invention, rapid backlight lamp bead optical quality detection can be realized for Mini LED backlight plates of any large-size backlight lamp bead array, and the detection efficiency and the detection precision are improved.

The utility model relates to test device technical field, and disclose a kind of testing device for rubber sealing element production, including test box, water pump and air heater.Test box top plate lower surface installs cylinder, its output end installs sealing plate, and there is test seat in test box inner chamber middle part, cylinder can drive sealing plate to lift, can flexibly adjust and test seat cooperation state, satisfy different extrusion test demand.Water pump is located on test box inner chamber baffle upper surface, water outlet is communicated with the inside of sealing plate through delivery pipe, cooperate the pressure sensor and data acquisition module on the upper surface of sealing plate, can real-time acquisition monitoring water pressure data, provide basis for quality detection.Air heater is located at test box air inlet, and air outlet is connected heating frame through gas pipe, can heat the air entering test box, provide different temperature environment, expand test range, and sealing plate cooperation can more accurately test rubber sealing element quality.

The application relates to the technical field of steel structure installation and construction of thermal power plants, in particular to a steel coal hopper installation method, which comprises the following steps: coal hopper segmentation prefabrication: the coal hopper is divided into an upper hopper body section, a lower hopper body section and a cone section; lower hopper body section hoisting: hoisting the lower hopper body section to a coal hopper beam; cone penetration: hoisting the cone section so that the cone section penetrates through the lower hopper body section; upper hopper body section hoisting: hoisting the upper hopper body section to the lower hopper body section and welding the upper hopper body section and the lower hopper body section; finishing: welding the upper end of the cone section and the lower end of the lower hopper body section. The application adopts an inverse sequence penetration mode of "first middle, then lower and finally upper" to complete the segmented hoisting of the square-to-round transition steel coal hopper, and solves the problems that the traditional hoisting sequence cannot independently support the cone and it is difficult to perform high-altitude butt welding.

The present application provides a quality control system and method for foamed asphalt mixture, which relates to the field of intelligent detection. It uses machine vision-based image recognition and detection technology to grid-cut the sample image after the foamed asphalt mixture is compacted and semantically encode the local image blocks of the sample performance, and then perform spatial semantic enhancement on the semantic encoding features of the local image blocks of each sample performance, so as to intelligently judge whether the material performance meets the preset standards based on the energy global aggregation of the semantic enhancement features of the local image blocks of each sample performance after spatial semantic enhancement. In this way, by analyzing the image of the entire sample area, the quality of the overall material can be fully reflected. At the same time, it can detect subtle defects that may be overlooked by traditional methods, thereby achieving comprehensive, accurate and intelligent quality control of foamed asphalt mixture.

The invention relates to the technical field of intelligent control, and discloses a turn-to-turn slot jumping control method and system for a numerical control winding machine, and the system comprises the steps: collecting the data of a to-be-turned wire through a collection unit, and determining the rotating speed of a main shaft motor according to the data of the to-be-turned wire; the judgment unit acquires image data at the winding mold based on the image acquisition device to obtain the flatness of the wire harness, and judges whether the winding pre-tightening force is adjusted or not; the processing unit identifies the first slot position and the second slot position according to the image data, determines the center distance, and determines the moving distance of the to-be-wrapped wire controlled by the stepping motor according to the center distance; the processing unit collects second image data at the winding mold after the envelope jumps out of the groove and judges whether wire harness crossing exists or not according to the second image data; and adjusting the moving distance according to the crossed wire harness when the wire harness is judged to be crossed. Through cooperative work of the multifunctional modules, more accurate wire harness positioning and winding quality control are achieved, the requirement for manual intervention is reduced, and the production efficiency is improved.

The invention belongs to the technical field of traditional Chinese medicine honey refining process detection and analysis. The invention provides a honey refining process characterization method and system based on near infrared spectrum and color characteristics. The method comprises the following steps: acquiring near infrared spectrum data and corresponding color images of a sample in a flow cell through an outer circulation pipeline; extracting low-dimensional color features from the image, coupling and fusing the low-dimensional color features with the preprocessed spectral data, and constructing a honey refining process state characterization vector; establishing a partial least squares regression model as a main model, and introducing an extreme gradient lifting model as nonlinear supplement to obtain a comprehensive characterization result; and performing variable contribution analysis on the double models by utilizing a hierarchical interpretation framework, and verifying the consistency of a model prediction mechanism and a physical and chemical reaction path in a honey refining process. According to the method, spectrum and visual information are fused, linear and nonlinear modeling advantages are combined, reliability of a model mechanism is ensured through interpretability analysis, and a new way is provided for accurate monitoring of the honey refining process.

The invention discloses a chemical product quality prediction method and device, equipment and a storage medium, and relates to the field of industrial big data. The method comprises the following steps: acquiring process operation parameters and actually measured quality parameters of a chemical product in a production process; based on the process operation parameters and the actually measured quality parameters, a training sample of the product quality prediction model is generated, and sample data of the training sample comprises the process operation parameters; wherein the product quality prediction model is an artificial intelligence model constructed based on a limit gradient lifting tree algorithm; training the product quality prediction model by adopting the training sample to obtain a trained product quality prediction model; wherein the trained product quality prediction model is used for predicting the quality of the chemical product. According to the method, the product quality prediction model based on the limit gradient boosting tree algorithm is trained, so that the quality of the chemical product is predicted, and the labor cost and the medicament consumption are reduced.

The invention discloses a decoration project inspection system based on a bionic robot dog, relates to the technical field of decoration project inspection, and aims to significantly reduce manual inspection time and labor cost through autonomous inspection of the robot dog, improve the overall acceptance efficiency, collect and analyze data in real time, quickly generate a detection result and improve the inspection efficiency. Delay in a traditional method is avoided, the AI technology and image recognition are utilized, interference of human factors is systematically eliminated, objectivity and consistency of acceptance results are ensured, decoration quality is accurately recognized and evaluated through a high-precision sensor and an algorithm, the risks of missing detection and misjudgment are reduced, and the efficiency is improved through an automatic process. The acceptance personnel can concentrate more energy on important decision and management, the working efficiency is improved, the application of the system conforms to the development direction of buildings and smart cities, and the building industry is promoted to develop in the more efficient and more intelligent direction.

The invention relates to an electric power image sample data processing method and device based on a large model, and a storage medium, and the method comprises the steps: obtaining an electric power image, extracting low-level features and high-level features through a convolutional neural network, and taking the features as image features; taking the image features and pre-acquired power field knowledge base information as input of a pre-trained large model, generating label information, obtaining a real sample, and realizing annotation of the power image; in the labeling process, probability distribution is introduced by using a Bayesian neural network, so that logarithm likelihood estimation is maximized, and the uncertainty of labeling is reduced; a generative adversarial network is trained with the target that a discriminator cannot distinguish the generated sample and the real sample, a new power image is generated by using the trained generative adversarial network, and the generated sample is obtained through labeling; and in combination with the mean absolute error and the Frechet distance, evaluating the similarity and the distribution consistency of the real sample and the generated sample.