71results about How to "Remove distortion" patented technology

The invention relates to the field of image enhancement, in particular to an image enhancement method and system of a vehicle-mounted image sensor. The method comprises the following steps: acquiring driving record images of a vehicle at multiple angles; dynamic scene self-adaptive exposure adjustment is carried out on the driving record images of the vehicle at the multiple angles, so that multiple self-adaptive exposure driving images are obtained; carrying out deep network noise identification on the plurality of adaptive exposure driving images, and carrying out dynamic filtering and noise reduction on sub-images one by one so as to generate a plurality of filtering and noise reduction optimized images; carrying out image texture analysis on the plurality of exposure sub-images, and carrying out texture distortion reconstruction to construct a plurality of texture reconstruction images; and road object visual identification is carried out on the plurality of texture reconstruction images, and adaptive contrast enhancement processing is carried out, so that a plurality of detail contrast enhancement images are constructed. According to the invention, a high-definition and stable panoramic vehicle-mounted image is realized.

The invention provides a vehicle-mounted navigation panoramic video stitching method and system, and belongs to the technical field of auxiliary driving, and the method comprises the following steps: obtaining vehicle periphery original images of a vehicle body in multiple directions in real time; performing image distortion correction on the plurality of original images around the vehicle to obtain a plurality of overlook view angle images for splicing; and dividing the plurality of overlook view angle images into overlapped areas and non-overlapped areas by adopting a partition gradual-in and gradual-out weighted fusion method, retaining image information of the non-overlapped areas, performing weighted distribution on gray weight information of the overlapped areas, and fusing the overlapped areas according to a distributed gray value to obtain a spliced panoramic image around the vehicle body. According to the method, the visual blind area existing during turning, overtaking and side parking can be solved, potential safety hazards are greatly eliminated, meanwhile, ghosting or distortion occurring in the overlapping area can be eliminated, the splicing effect of the panoramic spliced image is improved, and a driver can make correct judgment conveniently.

The invention discloses a confocal microscope camera calibration method based on high-precision motion control. The confocal microscope camera calibration method mainly comprises the steps of establishing four coordinate systems, placing a checkerboard calibration plate on a high-precision platform and adjusting the checkerboard calibration plate to the center of the view of a camera, and shooting and recording image coordinates of a calibration point. And based on the imaging relationship between the optical center of the camera and the object point, determining the mapping relationship between the coordinate systems so as to establish a preliminary imaging model. Then, nonlinear correction is performed on the imaging model, lens distortion is eliminated, and corrected image coordinates are converted into pixel coordinates. The non-linear correction parameters are optimized through the multi-view data, the mapping relation between the image plane and the platform physical plane is further calculated, and the mapping relation is optimized through the least square method so as to improve the calibration precision. Finally, pixel coordinates in the image are converted into physical coordinates of a platform through the optimized matrix, and support is provided for the automatic focusing process of the confocal microscope.

The invention relates to the field of data processing, in particular to an environment perception data processing method and system based on an intelligent helmet. The method comprises the following steps: acquiring a scene image in front of a user and multi-source environment real-time sensing data; performing scene attribute state analysis on the multi-source environment real-time sensing data, and constructing a real-time scene attribute state diagram; performing contrast dynamic balance adjustment on the scene image in front of the user, performing super-resolution fusion reconstruction, and constructing a super-resolution scene image; performing object visual identification on the super-resolution scene image, and performing object bounding box segmentation processing to obtain a plurality of accurate scene object bounding boxes; and carrying out optical flow motion change analysis on the plurality of accurate scene object bounding boxes, and carrying out space-time scene structure evolution analysis so as to obtain dynamic scene evolution characteristic data. According to the method, the data processing efficiency of the environment perception data is improved, and the environment perception data is visualized more visually.

The invention relates to the technical field of projectors, in particular to a projector control method and a projector. The method comprises the following steps: performing image projection signal processing on target projection image data to generate initial projection picture data; performing projection point cloud space-time registration on the initial projection picture data by using the dual laser radar assembly to obtain projection scanning point cloud space data; performing shielding area geometric feature analysis on the projection scanning point cloud spatial data, determining an ideal projection area, and generating ideal rectangular projection area data; performing intelligent projection control parameter processing on the ideal rectangular projection area data to obtain intelligent projection control parameters; and performing projection attitude control instruction processing on the intelligent projection control parameters to obtain projection control optimization effect data. According to the invention, the projection control parameters are automatically adjusted through intelligent identification of the projection surface, so that the projector can maintain a stable projection effect in different environments, and the quality of a projection image is remarkably improved.

The invention discloses a confocal microscopic image distortion correction method based on a two-axis MEMS (Micro Electro Mechanical System) scanning galvanometer. The method comprises the following steps: acquiring an original image by using a confocal microscope of a two-axis MEMS scanning galvanometer; calculating to obtain a galvanometer normal vector; calculating to obtain an incident light unit vector; calculating to obtain a reflected light unit vector; according to the method, distortion introduced by the MEMS galvanometer can be removed, distortion introduced by the MEMS galvanometer can be corrected under the condition that the posture of the scanned end face is unknown, and then a distortionless confocal image is obtained.

The invention discloses a remote control anti-delay video transmission method based on a future scene generation network. The remote control anti-delay video transmission method comprises the following steps: synchronizing time references of a remote control vehicle and a remote cockpit; original video stream data of the environment where the remote control vehicle is located is collected; adding a camera number and timestamp information into the original video stream data; preprocessing the decoded video stream data to generate a plurality of paths of future scenes; generating multiple paths of future scene video stream data; camera numbers and timestamp information are added to the multiple paths of future scene video streams; decrypting, decoding and distributing the data; performing packet loss and time delay detection on the original video stream data, and performing visual quality optimization on the future scene video stream data; and a complete and continuous video stream is formed. According to the method, the delay in video transmission is greatly reduced, and the video content at the future moment can be predicted and generated in advance in future scene generation, so that the video blank possibly occurring due to transmission delay or data packet loss is effectively filled.

The invention discloses an unmanned vehicle ground point cloud segmentation method in an unstructured environment, and belongs to the technical field of vehicle automatic driving. The ground point cloud segmentation method comprises the following steps: S1, preprocessing original laser radar point cloud data; iMU pre-integration is adopted to carry out motion distortion correction on the laser radar point cloud, and the point cloud height and the reflection intensity are utilized to remove ground noise; and S2, segmenting the ground point cloud. The method comprises the following steps of: dividing a radar sensing area by using a dynamic Concentric Zone Model (DCZM); and segmenting the ground point cloud through ground initial fitting point screening and a ground fitting algorithm. According to the invention, more accurate ground point cloud segmentation in a non-structural environment is realized.

The invention discloses a hyperspectral remote sensing mineralization alteration information extraction method, device and equipment and a medium, and is applied to the technical field of remote sensing geological survey, the hyperspectral remote sensing mineralization alteration information extraction method comprises the following steps: obtaining sample laboratory spectral data and sample hyperspectral satellite remote sensing data of a rock and soil sample; calculating the sample laboratory spectral data and the sample hyperspectral satellite remote sensing data by adopting a direct standardization algorithm, and determining a transfer matrix required for converting the sample hyperspectral satellite remote sensing data into the sample laboratory spectral data; based on the transfer matrix, converting hyperspectral satellite remote sensing data of a research area to obtain laboratory-like spectral data of the research area; and performing similarity analysis on the laboratory-like spectral data and the standard spectral data of the altered mineral, and determining mineralization alteration information in the laboratory-like spectral data.

The invention relates to the technical field of data analysis, in particular to a driving assistance system based on vehicle-mounted 360-degree panoramic monitoring, which comprises a camera calibration module, a camera correction module, a dynamic shielding monitoring module, a shielding object recognition module and a remote server, four vehicle-mounted cameras are calibrated and calculated, so that the imaging precision of the cameras is improved; through image distortion correction, subsequent image processing and analysis are facilitated; an image processing algorithm is utilized to obtain a shielding area, quantitative analysis is carried out, and a data source is provided for shielding object recognition; according to the method, feature extraction is carried out on a shelter, the threat level is evaluated, and an identification result is generated, so that potential dangers can be timely warned; and early warning analysis is carried out according to the shielding object identification result, so that the response speed and accuracy of the system to potential threats are improved. The method and the device are used for solving the technical problem of insufficient monitoring efficiency caused by camera distortion and inaccurate dynamic shielding identification of the current vehicle-mounted camera.

The invention relates to a digital holographic microscopic distortion compensation method and system combined with deep learning. According to the method, a deep learning image segmentation technology and a phase distortion compensation technology are fused, an off-axis transmission-type digital holographic microscopic system is built, a hologram is shot to serve as a data set, then a U-net convolutional neural network is improved, and the improved U-net convolutional neural network is trained by using the data set; and segmenting the tested sample and the background in the hologram, and fitting the unwrapped background phase by using the least square based on the Zernike polynomial so as to realize phase distortion compensation. The invention further provides a digital holographic microscopic distortion compensation system combined with deep learning. The system comprises a module training module, an image processing module and a phase compensation module. Compared with the prior art, the method has the advantages of effectively eliminating distortion generated by the digital holographic system, improving efficiency, improving accuracy, saving calculation cost, improving network training effect and generalization ability and the like.

The invention discloses a corn emergence rate calculation method and system based on unmanned aerial vehicle remote sensing images and machine learning, and relates to the field of corn emergence rate calculation. The problems that errors exist when corn seedlings are extracted and recognized through existing unmanned aerial vehicle remote sensing images, pertinence is not high when a common plant seedling rate detection method is used, and the corn seedlings are difficult to recognize at the initial stage are solved. The method comprises the following steps: constructing an aerial image data set; performing wave band registration, general DSM, single orthoimage, mosaic orthoimage and radiation calibration on the aerial image data set, and then completing splicing; performing color transformation on the spliced image to obtain a binary image; extracting corn features in the binary image according to threshold segmentation and image scale scaling transformation; calculating the number of corn seedlings and the emergence rate extracted by the unmanned aerial vehicle according to the seeding quantity; and constructing a corn emergence rate model according to a random forest algorithm and the actual emergence rate, and obtaining the emergence rate according to the corn emergence rate model. The method is applied to the agricultural field.

The present invention belongs to the field of medical image processing, and provides a method, system and medium for processing medical endoscopic images based on GPU. The present invention utilizes the powerful parallel processing capability of GPU to significantly improve the speed and accuracy of endoscopic image acquisition, preprocessing, feature point detection, image correction and pathological feature recognition. The image quality is enhanced by executing GPU-accelerated filtering algorithms and histogram equalization, while the GPU-optimized SIFT algorithm effectively improves the accuracy of feature point matching. The estimation of the affine transformation model and the transformation correction of the image further correct the distortion and ensure the accuracy of the image data. Finally, the pre-trained deep learning model is used to implement fast convolutional neural network forward propagation on the GPU, identify pathological features in real time, and assist clinical diagnosis. The efficiency and accuracy of clinical diagnosis are greatly improved, providing doctors with instant diagnostic assistance, thereby improving the quality of medical services.

The application provides a big data-based intelligent manufacturing supply chain management system and method. A cloud big data engine is used to jointly model supplier capacity, logistics timeliness and historical abnormal events based on multi-source data flow of a manufacturing supply chain, and generate a risk probability matrix of material shortage in multiple supply chain nodes. When the risk probability of material shortage of a supply chain node exceeds a material shortage threshold, a risk decision is made on the risk probability matrix and the work-in-process cache amount as a joint state space, with the goal of minimizing total interruption cost and maximizing delivery rate, and a material shortage scheduling scheme of the manufacturing supply chain is output. The material shortage scheduling scheme is distributed to corresponding suppliers and logistics parties through a blockchain smart contract, and order splitting and payment binding are automatically executed to complete the material shortage scheduling of the supply chain. Based on the above scheme, multi-objective autonomous scheduling of material shortage risk of the manufacturing supply chain can be realized, thereby improving the anti-disturbance capability of the manufacturing supply chain under interruption environment.

The invention discloses a tension testing device for cable detection, and relates to the field of tension testing devices, the tension testing device comprises a testing rack, the testing rack is movably provided with a testing pull-up seat, and the testing pull-up seat is provided with a pull-up clamp; the device further comprises a cable position detection device, and the cable position detection device is installed on the test rack. It needs to be explained that in the embodiment of the invention, sudden stop is triggered through mechanical swing of the cable holder, the skew fault can be identified in the initial stage, the tension coaxiality deviation caused by skew cable clamping and deformation and sinking of the pull-up seat is avoided, and the major safety accident of cable collapse is effectively avoided; according to the cable tension test device, the test data distortion caused by such factors is eliminated, the accuracy and repeatability of a cable tension test result are ensured, meanwhile, through reverse mechanical triggering, real-time detection and sudden stop of tiny deformation and sinking of the pull-up seat are realized, and hidden safety hazards are eliminated in advance.

The utility model provides a kind of clamping mechanism for building window wind pressure detection equipment, including mounting plate frame and two side clamping devices;Two side clamping devices are symmetrically arranged on the left and right sides of mounting plate frame, and the bottom of side clamping device is used to clamp the window to be measured;Side clamping device includes side positioning assembly, linkage type clamping mechanism, multiple electric push rods, multiple push plates and multiple buffer assemblies, multiple electric push rods are arranged below mounting plate frame, the fixed end of electric push rod is connected with the lower end surface of mounting plate frame, the output end of electric push rod is connected with push plate, and the lower end surface of each push plate is correspondingly provided with a buffer assembly, and the bottom of buffer assembly is connected with side positioning assembly.The clamping mechanism for building window wind pressure detection equipment of the utility model solves the problem of insufficient local locking force during multi-point clamping of the clamping mechanism in related technology, which can easily cause micro-displacement or stress concentration deformation of the test piece.

The invention provides a railway tunnel panorama synthesis monitoring method and device, equipment and a medium. The method comprises the following steps: collecting a plurality of groups of initial image sequences of each road section; performing fusion processing on the plurality of initial images in each group to obtain a fused image; splicing the plurality of fused images to obtain an initial road section image; and post-processing the initial road section image to obtain a target road section image. The initial images of different angles and exposures are collected, the influence of the dark environment of the tunnel is reduced, and the authenticity of the images is improved. And the initial image is fused, so that the processing process of redundant information is reduced, and the processing efficiency is improved. When the fused image is spliced, the important edge structure is extracted, the extraction process is simplified, and the processing speed is improved. And the structural deformation of the fused image is limited, so that the splicing stability is ensured, and the structural distortion is avoided. And through post-processing, distortion and distortion of the image edge are eliminated, and the overall visual effect is improved.

The embodiments of the present disclosure disclose a camera parameter calibration method, device, electronic device and computer-readable medium. A specific implementation of the method includes: obtaining a parameter set to be calibrated; constructing camera calibration scene information; controlling the camera fixing device to move to a preset shooting angle set to obtain a two-dimensional code image set; based on the two-dimensional code image set, executing the following camera calibration steps: extracting feature points from the two-dimensional code image set to obtain multiple image feature point sets; determining two-dimensional pixel coordinates and three-dimensional space coordinates; generating a camera internal parameter set; determining a camera external parameter set; determining a three-dimensional coordinate set of corner points corresponding to the target two-dimensional code image; determining a coordinate error; in response to determining that the coordinate error is within a preset coordinate error range, completing the parameter calibration of the camera to be calibrated. This implementation can reduce the cost and time of camera calibration, and improve the versatility and accuracy of camera calibration.

The invention provides a binocular ranging temperature compensation method based on fusion of a rank image and a YCbCr image. The binocular ranging temperature compensation method comprises the following steps: calibrating and correcting an acquired binocular visible light image and an infrared image; converting the corrected visible light image into a rank image; a YCbCr image is obtained; according to the rank image and the YCbCr image, performing image matching by using a difference function fused by a local feature difference value and a color difference value to obtain a disparity map; obtaining the three-dimensional position of each point by using a triangulation method according to the obtained disparity map and calibration parameters of the camera; identifying the target terminal according to the corrected infrared image to obtain a position area of the target terminal, and extracting temperature information in the identified position area of the target terminal to obtain a measured temperature value of the target terminal; and obtaining a distance value of the target terminal in the infrared image, and compensating the measurement temperature of the target terminal by using the distance value. The accurate distance value of the cable terminal can be obtained, and the interference of distance factors on the temperature value measured by the infrared camera is eliminated.

The utility model relates to the technical field of building material production, and discloses a drawing machine for processing a steel bar, which comprises a workbench, a sliding chute is arranged in the workbench, a sliding block is movably arranged in the sliding chute, a two-way screw rod is movably arranged in the sliding block, the two-way screw rod completely penetrates through the interior of the workbench, and the two-way screw rod is movably arranged in the sliding chute. A manual rocker is fixedly installed at one end of the sliding groove. Compared with a traditional drawing machine, the drawing machine has the advantages that the distance between the two straightening wheels can be conveniently adjusted through the cooperation of the bidirectional lead screw and the sliding block, flexible adjustment can be achieved according to the diameter of a bar and the drawing requirement, it is ensured that the bar bears proper straightening force when passing through the drawing machine, bending or distortion of the bar is effectively eliminated, and if the distance is too short, the drawing machine is not prone to deformation. In the prior art, straightening force may be too large, bar stress is increased, even breakage is caused, straightening force is insufficient if the distance is too long, and an ideal straightening effect is difficult to achieve.

The invention belongs to the technical field of optical detection and color measurement, and particularly relates to a chromatic aberration measurement method and system based on hyperspectral global scanning imaging and a storage medium. Comprising the following steps: acquiring a hyperspectral scanning result of a to-be-detected chromatic aberration sample including a hyperspectral scanning sub-image; splicing the to-be-spliced hyperspectral scanning images to obtain a global hyperspectral scanning result of the to-be-detected chromatic aberration sample; the hyperspectral scanning image to be spliced is a hyperspectral scanning sub-image or an intermediate image formed by splicing; the splicing method comprises the following steps: carrying out feature point detection on a to-be-spliced hyperspectral scanning image to obtain a feature point descriptor set of the to-be-spliced hyperspectral scanning image, matching the feature point descriptor set of the to-be-spliced hyperspectral scanning image, and carrying out two-dimensional rigid body coordinate transformation based on a matching result to obtain the to-be-spliced hyperspectral scanning image. The hyperspectral scanning images to be spliced are spliced; and performing chromatic aberration calculation on the global spectrum scanning image of the chromatic aberration sample to be detected and the standard sample to obtain a chromatic aberration calculation result.

The utility model relates to the technical field of gas extraction, specifically relates to a directional drilling field gas extraction pipeline optimization system, mainly solves the online measurement device measurement error of existing directional drilling field gas extraction pipeline is bigger and the technical problem of data distortion. The system includes extraction pipeline, adapter tee, measuring pipeline, online measurement device, connecting pipeline and negative pressure branch pipe, through the position of adapter tee changes to with the drill site chamber to form the installation area, then sets up measuring pipeline to install online measurement device in the installation area, since the installation area is located in the roadway, and the space is sufficient, so can satisfy 'front 7 back 4 times pipe diameter' straight section installation condition, thereby can reduce the measurement error of online measurement device, simultaneously, can eliminate the measurement data distortion caused by airflow interference to the downstream of online measurement device.

The present application relates to the field of machine vision technology, and discloses a control system and method for adaptively adjusting the intensity of a machine vision light source. The method comprises: using different multiple first light source intensities to respectively perform video frame acquisition and preprocessing on multiple first objects of different sizes, and obtain target video frame data; establishing a relationship model; when a second object is detected, dynamically adjusting the light source intensity, obtaining the second light source intensity and obtaining real-time video frame data; performing object detection, obtaining object detection data and performing light source control strategy analysis, and obtaining a total light source control strategy; obtaining multiple point light source control nodes and performing control parameter allocation, and obtaining multiple initial point light source control parameters; performing light source intensity control modeling and parameter optimization through multiple initial point light source control parameters, and obtaining multiple target point light source control parameters of the second object. The present application improves the control accuracy of adaptively adjusting the intensity of a machine vision light source.

This invention relates to the field of electronic nautical chart system technology and discloses an electronic nautical chart mapping and printing method based on the QT framework, which solves the problems of low data retrieval efficiency, display distortion, poor format adaptability and insufficient interactivity in the prior art. It includes the following steps: (1) Dynamic data filtering based on Rtree spatial indexing technology, quickly locating geographic elements of the target area through full-map printing or box-selection printing modes, and dynamically calculating the scale and coordinate parameters; (2) Intelligent drawing of nautical chart elements using SVG vector format, integrating latitude and longitude scales, north arrow, legend, scale, and nautical chart image drawing, and dynamically configuring production information, element visibility, and font style through QT controls; (3) Interactive preview supports adaptive scaling, multi-mode display settings, and cross-format output, and can generate high-precision vector PDF printables or pixel PDF schematic diagrams. This invention can be applied to the printing module of an electronic nautical chart system based on the QT framework.

The utility model relates to an olivary air hole alloy saw blade. The olivary air hole alloy saw blade comprises a base body and tool bits. An olive-shaped air hole is formed in the middle of the base body; the air holes are uniformly distributed along the circle center of the substrate; each air hole is composed of two semi-ellipses with coincident long axes. 1 / 2 of the long axis of the ellipse close to the outer circle of the base body is C1, 1 / 2 of the long axis of the ellipse close to the center position of the base body is C2, and C2 is larger than or equal to C1; the dimension of the short axis is B, B: (C1 + C2) = 0.25-0.75, and the long axis of the ellipse is arranged along the radial direction of the base body; the distance between the outermost vertex of the outer ellipse of the air hole and the bottom circle of the chip pocket of the base body is L, and L is larger than or equal to 10% * D2 and smaller than or equal to 20% * D2; the distance between the innermost vertex of the ellipse in the air hole and the center of the base body is L1, and L1 is larger than or equal to 15% * D2 and smaller than or equal to 25% * D2; the beneficial effects of the utility model are that the olivary air holes are closer to the sector, which is beneficial to the uniformity of tangential strain in the radius direction and improves the additional tangential stress generated by uneven tangential strain in the radius direction; the curvature radius of the radial edge of the olive-shaped air hole is large, so that the circumferential pressure stress is released more thoroughly.

This application provides a pupil recognition method, system, medium, product, and terminal based on center localization. It performs a horizontal gradient transformation operation on distortion-corrected human eye image data to generate eye gradient amplitude image data. Through gradient transformation, it extracts edge features of the pupil and iris regions, effectively separating the pupil edge from complex eye structures such as eyelid occlusion, eyelash projection, and iris pigment spots / crypts, avoiding misidentification of these interferences as pupil edges and improving the accuracy of pupil edge feature recognition. Combining the distortion-corrected human eye image data and eye gradient amplitude image data, it performs a pupil template matching operation based on the Hough circle detection algorithm. By leveraging the edge features of the gradient amplitude image, it enhances the matching accuracy between the pupil edge and the template, effectively ensuring the continuity and integrity of pupil contour recognition, further improving the reliability and accuracy of pupil measurement results.

The application provides an instrument identification method, computer equipment, a storage medium and a computer program product. The method first crops the instrument region in the inspection image, removes background interference, and obtains an image highlighting the instrument. Then, the cropped image is input into an end-to-end correction model to directly generate a front view image through a single forward propagation, avoiding error accumulation of traditional multi-stage methods and improving the robustness of the correction from the architecture. In the model training stage, the reading result of the front view image output by the correction model is taken as a supervision signal by a multi-modal large language model, which on the one hand distills the geometric and semantic understanding ability of the large model to the lightweight model, and on the other hand makes the correction model directly optimize the reading accuracy instead of only focusing on image similarity. This training strategy significantly improves the performance of the model under complex working conditions such as inclination, occlusion and dramatic changes in illumination. Finally, based on the corrected front view image, the reading recognition is performed, which greatly improves the accuracy and stability of the instrument reading.

The invention discloses an unmanned aerial vehicle-mounted water depth measurement continuous frequency conversion blue-green laser radar according to the characteristic that continuous frequency conversion blue-green laser generates frequency change when encountering a water surface and a water bottom, convolution and fast Fourier transform and a time-frequency corresponding relation. The system is composed of a blue-green light frequency conversion laser, a laser power supply driver, a coding motor, a reflective optical wedge, a reflector, a large lens, a small lens, a balance light detection module, a high-speed laser acquisition processor, an IMU module, an RTK module, a 4G module, a controller, a 4G antenna, a server, a mobile phone terminal and the like. The laser radar is small in size, light in weight and suitable for the unmanned aerial vehicle to measure the water depth rapidly and precisely, the precision can reach the millimeter level, and 0-10 m water depth measurement can be achieved.

The invention relates to the technical field of industrial control network security, in particular to an industrial control network intelligent exposed surface identification and risk assessment system and method, and the system comprises a data collection module, a data processing module, an equipment management module and an analysis module. And setting a data label for each device based on the operation parameter of each device in the industrial control network monitored by the data acquisition module, each data label representing the operation condition of the corresponding device, processing each device based on the counted number of devices of each data label and the fluctuation parameter, and when it is determined that the operation of each device is abnormal, determining that the operation of each device is abnormal. The operation environment of each device is adjusted in time to ensure stable operation of each device in the industrial control network, the device with the exposed surface is found in time, each device is adaptively processed, the accuracy of exposed surface identification is improved, and the identification efficiency of the exposed surface is further improved.

This invention relates to the field of performance evolution analysis technology, specifically to a method and system for analyzing the performance evolution of wire harness connections. The method includes the following steps: acquiring various operational data corresponding to wire harness connection nodes and generating a multi-dimensional time-series dataset based on the data acquisition time sequence; performing time-series calibration on the multi-dimensional time-series dataset and simultaneously constructing a wire harness connection parameter correlation matrix; generating a set of wire harness performance correlation coefficients based on the wire harness connection parameter correlation matrix; establishing a wire harness connection performance evolution model based on the set of wire harness performance correlation coefficients, iteratively training the wire harness connection performance evolution model using historical performance data, and generating model training parameters; predicting the evolution trend of the standardized time-series dataset based on the model training parameters, and generating a wire harness performance evolution trend curve; and performing evolution anomaly assessment and analysis based on the wire harness performance evolution trend curve, generating early warning information for wire harness connection performance anomalies. This invention can comprehensively improve the efficiency of wire harness connection status monitoring.