Coating compensation system based on visual coating quality inspection data
By acquiring, processing, and identifying images of coating quality inspection data from multiple angles, and combining this with infrared scanning to generate a coating compensation strategy, the problems of misjudgment and inaccurate compensation of coating defects in traditional visual inspection have been solved, achieving accurate coating compensation and smooth transition.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHENZJEM SOFTWELL TECH DEV CO LTD
- Filing Date
- 2026-06-05
- Publication Date
- 2026-07-10
AI Technical Summary
Traditional visual inspection is easily affected by the high reflectivity of the workpiece surface during coating processing, leading to misjudgment or missed detection of defects. Furthermore, it is difficult to accurately determine the type of defect and the feasibility of compensation, resulting in ineffective repairs.
The system employs a multi-angle visual coating quality inspection data acquisition, data processing, feature recognition, and coating compensation module. It combines light conversion coefficient to correct bright/dark areas, matches defect types based on gradient values, generates coating compensation strategies through infrared scanning, and uses an iterative closed-loop spraying strategy for precise compensation.
It effectively eliminates interference from reflections and shadows, enabling a qualitative detection process followed by a directional repairability assessment. This ensures accurate thickness compensation without underspray or overspray, eliminates the repair step effect, and guarantees a smooth transition of the coating.
Smart Images
Figure CN122368052A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of industrial spraying technology, specifically a coating compensation system based on visual coating quality inspection data. Background Technology
[0002] In the field of industrial coating processing, coating surfaces often suffer from defects such as scratches and incomplete coating due to process or environmental factors.
[0003] Traditional visual inspection is easily affected by the high reflectivity of the workpiece surface. Single-angle shooting often produces bright or dark areas, leading to misjudgment or missed detection of defects. Moreover, conventional vision can only identify the presence or absence of defects, making it difficult to accurately determine the type of defect and the feasibility of compensation, which can easily lead to ineffective repairs. Therefore, a coating compensation system based on visual coating quality inspection data is now provided. Summary of the Invention
[0004] The purpose of this invention is to provide a coating compensation system based on visual coating quality inspection data.
[0005] The objective of this invention can be achieved through the following technical solution: a coating compensation system based on visual coating quality inspection data, comprising: The image acquisition module is used to acquire multi-angle quality inspection data of the target workpiece; The data processing module is used to process multi-angle quality inspection data to obtain a fused image of the workpiece coating. The feature recognition module is used to extract features from the fused image of the workpiece coating and to calibrate the coating compensation area. The coating compensation module is used to generate a corresponding coating compensation strategy based on the infrared scanning data of the coating compensation area.
[0006] Furthermore, the process by which the image acquisition module acquires multi-angle quality inspection data of the target workpiece includes: A workpiece quality inspection area is set up, and an image acquisition module consisting of three image acquisition terminals and an environmental sensing terminal are deployed in the workpiece quality inspection area. The ambient brightness of the workpiece quality inspection area is obtained through an environmental sensing terminal. Images of the workpiece inspection area from different shooting angles are acquired by various image acquisition terminals. Images captured from different shooting angles by various image acquisition terminals are used as multi-angle quality inspection data.
[0007] Furthermore, the data processing module processes multi-angle quality inspection data to obtain a fused image of the workpiece coating, including: The captured images obtained by each data acquisition terminal are converted to grayscale and rasterized to obtain grayscale images corresponding to each captured image. Set up a sliding window to mark different regions within a grayscale image and obtain a local grayscale image; Select any local grayscale image and obtain the pixel values at each location in that local grayscale image; Based on the obtained pixel values, the linear physical brightness of the corresponding position within the local grayscale image is obtained; The obtained linear physical brightness is compared with the ambient brightness to obtain the light conversion coefficient; where the light conversion coefficient is the ratio of the physical brightness of the line to the ambient brightness. Set the conversion coefficient range, compare the obtained light conversion coefficient with the conversion coefficient range. If the light conversion coefficient is within the conversion coefficient range, it means that the corresponding position is normal. If the light conversion coefficient exceeds the upper limit of the conversion coefficient range, it means that the corresponding position is a bright spot. If the light conversion coefficient is lower than the lower limit of the conversion coefficient range, it means that the corresponding position is a dark spot. The highlights and shadows in the local grayscale image are summarized to determine the corresponding highlight and shadow areas. This process is repeated until all local grayscale images are processed, thereby obtaining the distribution of highlight and shadow areas in the grayscale image. The bright and dark areas in the grayscale image are corrected to obtain the corresponding corrected grayscale image. The common feature regions of the corrected grayscale images corresponding to the photos obtained by the three image acquisition terminals are identified, and the corrected grayscale images are fused according to the common feature regions to obtain the corresponding workpiece coating fused image.
[0008] Furthermore, the process of correcting the highlight and dark areas within the grayscale image to obtain the corresponding corrected grayscale image includes: Obtain the mask edges of the highlighted area and the normal area, as well as the pixel values inside the highlighted area, and then obtain the pixel values to be corrected at each position inside the highlighted area; The obtained pixel values to be corrected are filled into the corresponding positions inside the highlight area, thereby completing the correction of the highlight area; Based on the pixel values at each location in the dark area and the average pixel values of the local windows at each location, the enhanced pixel values at each location in the dark area are obtained. The corresponding positions in the dark area are filled with the obtained enhanced pixel values, thereby completing the correction of the dark area.
[0009] Furthermore, the process of identifying the common feature regions of the corrected grayscale images corresponding to the captured photos from the three image acquisition terminals, and fusing the obtained corrected grayscale images based on the obtained common feature regions to obtain the corresponding workpiece coating fused image includes: The edge regions of the workpiece within the corrected grayscale image are marked, and key features are extracted from the marked edge regions; the key features include the center point, convex corner, and concave corner of the workpiece edge region; The obtained key features are matched with the key features corresponding to another image acquisition terminal, and the same key features are determined based on the matching results. Based on the same key features, the common feature regions of each corrected grayscale image are determined. Based on the determined common feature regions, the corrected grayscale images corresponding to different image acquisition terminals are fused to obtain the corresponding workpiece coating fused image.
[0010] Furthermore, the process by which the feature recognition module extracts features from the fused image of the workpiece coating and calibrates the coating compensation area includes: Select a pixel threshold range, match the pixel values at each position of the workpiece coating fusion image with the selected pixel threshold range, and complete the binarization process of the workpiece coating fusion image based on the matching results to obtain the workpiece binarized image. Abnormal regions in the binarized image of the workpiece are marked, and noise is filtered out from the marked abnormal regions. A planar coordinate system is constructed for the binarized image of the workpiece, and the gradient values of the abnormal regions are obtained; Set up a defect type reference table, which includes defect types, gradient value ranges corresponding to each defect type, and corresponding compensation feasibility. The compensation feasibility includes compensateable defects and non-compensable defects. The gradient values of each abnormal region are matched with the gradient value ranges corresponding to each defect type in the defect type reference table to determine the defect type of the abnormal region and the corresponding compensation feasibility, thereby determining the corresponding coating compensation area.
[0011] Furthermore, the process by which the coating compensation module generates a corresponding coating compensation strategy based on the infrared scanning data of the coating compensation area includes: The coating compensation module is equipped with an infrared scanning unit, which marks the coating compensation area as the main compensation area. The main compensation area is scanned by the laser scanning unit, and the infrared scanning data of the main compensation area is obtained based on the scanning results. Based on the obtained infrared scanning data, the depth difference at each location within the main compensation area is obtained; Obtain the minimum value of the depth difference in the main compensation area, and obtain the required coating compensation amount at the corresponding location; Starting from this position, the coating amount of the coating compensation unit is set, and the coating compensation of the main compensation area is performed according to the set coating amount. After the coating compensation of the main compensation area is completed, the main compensation area after coating compensation is scanned again by the laser scanning unit. Then the above process is repeated until there is no depth difference in the main compensation area. A secondary compensation area is set at the edge of the main compensation area, and edge softening spraying compensation is applied to the secondary compensation area.
[0012] Furthermore, the positions at the edge of the main compensation area are summarized, tangents are drawn along each position, and the points perpendicular to the tangents and at a distance from the tangent point are marked as the boundary points of the secondary compensation area. This process is repeated to determine the boundary points of the secondary compensation area corresponding to all positions at the edge of the main compensation area. All the boundary points of the secondary compensation area are then connected sequentially to obtain the corresponding boundary lines of the secondary compensation area. The area between the boundary line of the secondary compensation area and the edge of the primary compensation area is defined as the secondary compensation area.
[0013] Compared with the prior art, the beneficial effects of the present invention are: 1. By collecting data from multiple angles and combining it with the light conversion coefficient, the bright / dark areas are corrected and fused, effectively eliminating interference from reflections and shadows; at the same time, based on gradient value matching of defect types and compensation feasibility, a leap from "qualitative detection" to "directional repairability judgment" is achieved, avoiding blind compensation; 2. Based on the depth difference obtained by infrared scanning, an iterative closed-loop strategy of "spraying-re-scanning" is adopted to ensure accurate compensation thickness without under-spraying or over-spraying; and a secondary compensation area is delineated for edge softening spraying, which eliminates the repair step effect and ensures a smooth transition between the compensation area and the normal coating. Attached Figure Description
[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.
[0015] Figure 1 This is a schematic diagram of the principle of the present invention. Detailed Implementation
[0016] like Figure 1 As shown, the coating compensation system based on visual coating quality inspection data includes: The image acquisition module is used to acquire multi-angle quality inspection data of the target workpiece; The data processing module is used to process multi-angle quality inspection data to obtain a fused image of the workpiece coating. The feature recognition module is used to extract features from the fused image of the workpiece coating and to calibrate the coating compensation area. The coating compensation module is used to generate a corresponding coating compensation strategy based on the infrared scanning data of the coating compensation area.
[0017] It should be further explained that, in the specific implementation process, the process by which the image acquisition module acquires multi-angle quality inspection data of the target workpiece includes: A workpiece quality inspection area is set up, and an image acquisition module and an environmental sensing terminal are deployed in the workpiece quality inspection area. The image acquisition module consists of three image acquisition terminals, which are respectively deployed at the top and diagonal of the workpiece quality inspection area. The ambient brightness of the workpiece quality inspection area is obtained through an environmental sensing terminal. Images of the workpiece inspection area from different shooting angles are acquired by various image acquisition terminals. Images captured from different shooting angles by various image acquisition terminals are used as multi-angle quality inspection data.
[0018] It should be further explained that, in the specific implementation process, the data processing module processes multi-angle quality inspection data to obtain a fused image of the workpiece coating, including: The captured images obtained by each data acquisition terminal are converted to grayscale and rasterized to obtain grayscale images corresponding to each captured image. A sliding window is set up to calibrate various regions within a grayscale image, thereby obtaining a local grayscale image. It should be noted that the sliding step size is the same throughout the grayscale image calibration process. Select any local grayscale image and obtain the pixel value at each position in that local grayscale image, denoted as Pixel; Based on the obtained pixel values, the linear physical brightness at the corresponding location within the local grayscale image is obtained, denoted as Xp, where: ; in It is an exponential factor; The obtained linear physical brightness is compared with the ambient brightness to obtain the light conversion coefficient; where the light conversion coefficient is the ratio of the physical brightness of the line to the ambient brightness. Set the conversion coefficient range, compare the obtained light conversion coefficient with the conversion coefficient range. If the light conversion coefficient is within the conversion coefficient range, it means that the corresponding position is normal. If the light conversion coefficient exceeds the upper limit of the conversion coefficient range, it means that the corresponding position is a bright spot. If the light conversion coefficient is lower than the lower limit of the conversion coefficient range, it means that the corresponding position is a dark spot. Example: Set the conversion coefficient range to [K1, K2]; Let K be the light conversion coefficient; When K < K1, it means that the corresponding position is a dark spot; When K > K2, it means that the corresponding position is a high-brightness point; When K1≤K≤K2, it means that the corresponding position is normal; The highlights and shadows in the local grayscale image are summarized to determine the corresponding highlight and shadow areas. This process is repeated until all local grayscale images are processed, thereby obtaining the distribution of highlight and shadow areas in the grayscale image. The bright and dark areas in the grayscale image are corrected to obtain the corresponding corrected grayscale image. The common feature regions of the corrected grayscale images corresponding to the photos obtained by the three image acquisition terminals are identified, and the corrected grayscale images are fused according to the common feature regions to obtain the corresponding workpiece coating fused image.
[0019] It should be further explained that, in the specific implementation process, the process of correcting the highlight and dark areas within the grayscale image to obtain the corresponding corrected grayscale image includes: For the highlighted area: Obtain the mask edges between the highlight area and the normal area, denoted as... The area inside the highlighted region is recorded as Let x be any position within the highlighted area, and let u(x) be the pixel value to be corrected at x. ; ; in, Here, v(x) represents the guide field, which is usually a smooth extension of the gradient field of the normal pixels outside the highlight area. The obtained pixel values to be corrected are filled into the corresponding positions inside the highlight area, thereby completing the correction of the highlight area; For the dark area: Let the pixel value of the dark area be denoted as The enhanced pixel value is obtained based on the dark area pixel value, and is denoted as . ,in: ; in For adaptive gain coefficients, This represents the average pixel value of a local window centered at point x. The size of the local window is set by technicians based on the actual situation. in, ; in This represents the pixel variance of the local window. This represents the noise floor variance of the image acquisition terminal. This is the gain limiting constant, typically taken as 3.0; The corresponding positions in the dark area are filled with the obtained enhanced pixel values, thereby completing the correction of the dark area.
[0020] It should be further explained that, in the specific implementation process, the process of identifying the common feature regions of the corrected grayscale images corresponding to the captured photos obtained by the three image acquisition terminals, and fusing the obtained corrected grayscale images based on the obtained common feature regions to obtain the corresponding workpiece coating fused image includes: The edge regions of the workpiece within the corrected grayscale image are marked, and key features are extracted from the marked edge regions; the key features include the center point, convex corner, and concave corner of the workpiece edge region; The obtained key features are matched with the key features corresponding to another image acquisition terminal, and the same key features are determined based on the matching results. Based on the same key features, the common feature regions of each corrected grayscale image are determined. Based on the determined common feature regions, the corrected grayscale images corresponding to different image acquisition terminals are fused to obtain the corresponding workpiece coating fused image.
[0021] It should be further explained that, in the specific implementation process, the feature recognition module extracts features from the fused image of the workpiece coating and calibrates the coating compensation area, including: Select a pixel threshold range, match the pixel values at each position of the workpiece coating fusion image with the selected pixel threshold range, and perform binarization processing on the workpiece coating fusion image based on the matching results to obtain a binarized workpiece image; it should be further noted that the pixel threshold range is obtained by taking photos of the qualified coated workpiece under different ambient brightness. The factors for selecting the pixel threshold range depend on the average ambient brightness obtained by the environmental sensing terminal. Example: The average ambient brightness obtained by the ambient sensing terminal is denoted as Lp, and the pixel threshold range corresponding to the average ambient brightness Lp is [R1,R2]. The pixel value is denoted as R. When pixel value R1≤R≤R2, then R=256; when R1>R or R>R2, then R=0. Abnormal regions in the binarized image of the workpiece are marked, and noise is filtered out of the marked abnormal regions. It should be noted that if the area of an abnormal region is smaller than a set value, the abnormal region is marked as noise and then removed. Only abnormal regions with an area not less than the set value are retained. A planar coordinate system is constructed for the binarized image of the workpiece, and the gradient value of the abnormal region is obtained. It should be noted that the gradient value refers to the ratio between the pixel value of the edge of the abnormal region (the pixel value before binarization) and the pixel value of the adjacent normal region (the pixel value before binarization). Specifically: Let c denote the edge of the anomaly region, and Kt denote the gradient value of the corresponding anomaly region, where: ; Where (x, y) are the coordinates of the edge of the anomaly region. This represents the pixel value at the coordinates corresponding to the edge of the abnormal region. For the pixel values corresponding to the normal region, L is the total length of the edge of the abnormal region; A defect type reference table is set up, which includes defect types, gradient value ranges corresponding to each defect type, and corresponding compensation feasibility. The compensation feasibility includes compensateable defects and non-compensable defects. The gradient values of each abnormal region are matched with the gradient value ranges corresponding to each defect type in the defect type reference table to determine the defect type of the abnormal region and the corresponding compensation feasibility, thereby determining the corresponding coating compensation area.
[0022] It should be further explained that, in the specific implementation process, the process by which the coating compensation module generates the corresponding coating compensation strategy based on the infrared scanning data of the coating compensation area includes: The coating compensation module is equipped with an infrared scanning unit, which marks the coating compensation area as the main compensation area. The main compensation area is scanned by the laser scanning unit, and the infrared scanning data of the main compensation area is obtained based on the scanning results. Based on the obtained infrared scanning data, the depth difference at each location within the main compensation area is obtained, denoted as... The depth difference refers to the height difference between each location within the main compensation area and the standard surface. Find the minimum value of the depth difference in the main compensation area, and obtain the required coating compensation amount at the corresponding location, denoted as . ,in: ; Where x and y are the coordinates corresponding to the minimum value of the depth difference; Starting from this position, the coating amount of the coating compensation unit is set, and the coating compensation of the main compensation area is performed according to the set coating amount. After the coating compensation of the main compensation area is completed, the main compensation area after coating compensation is scanned again by the laser scanning unit. Then the above process is repeated until there is no depth difference in the main compensation area. A secondary compensation area is set at the edge of the main compensation area, and edge softening spraying is applied to the secondary compensation area to eliminate any possible compensation boundary marks between the main compensation area and the normal area. Specifically: The coordinates and coating compensation amounts at each location along the edge of the main compensation area are summarized and recorded as follows: Tangents are drawn at each position, and points perpendicular to the tangent and at a distance from the tangent point are marked as the boundary points of the secondary compensation area. This process is repeated to determine the boundary points of the secondary compensation area corresponding to all positions on the edge of the main compensation area. All the boundary points of the secondary compensation area are then connected sequentially to obtain the corresponding boundary lines of the secondary compensation area. The area between the boundary line of the secondary compensation area and the edge of the primary compensation area is defined as the secondary compensation area.
[0023] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications or equivalent substitutions made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.
Claims
1. A coating compensation system based on visual coating quality inspection data, characterized in that, include: The image acquisition module is used to acquire multi-angle quality inspection data of the target workpiece; The data processing module is used to process multi-angle quality inspection data to obtain a fused image of the workpiece coating. The feature recognition module is used to extract features from the fused image of the workpiece coating and to calibrate the coating compensation area. The coating compensation module is used to generate a corresponding coating compensation strategy based on the infrared scanning data of the coating compensation area. The process by which the image acquisition module acquires multi-angle quality inspection data of the target workpiece includes: A workpiece quality inspection area is set up, and an image acquisition module consisting of three image acquisition terminals and an environmental sensing terminal are deployed in the workpiece quality inspection area. The ambient brightness of the workpiece quality inspection area is obtained through an environmental sensing terminal. Images of the workpiece inspection area from different shooting angles are acquired by various image acquisition terminals. Images captured from different shooting angles by various image acquisition terminals are used as multi-angle quality inspection data.
2. The coating compensation system based on visual coating quality inspection data according to claim 1, characterized in that, The data processing module processes multi-angle quality inspection data to obtain a fused image of the workpiece coating, including the following steps: The captured images obtained by each data acquisition terminal are converted to grayscale and rasterized to obtain grayscale images corresponding to each captured image. Set up a sliding window to mark different regions within a grayscale image and obtain a local grayscale image; Select any local grayscale image and obtain the pixel values at each location in that local grayscale image; Based on the obtained pixel values, the linear physical brightness of the corresponding position within the local grayscale image is obtained; The obtained linear physical brightness is compared with the ambient brightness to obtain the light conversion coefficient; where the light conversion coefficient is the ratio of the physical brightness of the line to the ambient brightness. Set the conversion coefficient range, compare the obtained light conversion coefficient with the conversion coefficient range. If the light conversion coefficient is within the conversion coefficient range, it means that the corresponding position is normal. If the light conversion coefficient exceeds the upper limit of the conversion coefficient range, it means that the corresponding position is a bright spot. If the light conversion coefficient is lower than the lower limit of the conversion coefficient range, it means that the corresponding position is a dark spot. The highlights and shadows in the local grayscale image are summarized to determine the corresponding highlight and shadow areas. This process is repeated until all local grayscale images are processed, thereby obtaining the distribution of highlight and shadow areas in the grayscale image. The bright and dark areas in the grayscale image are corrected to obtain the corresponding corrected grayscale image. The common feature regions of the corrected grayscale images corresponding to the photos obtained by the three image acquisition terminals are identified, and the corrected grayscale images are fused according to the common feature regions to obtain the corresponding workpiece coating fused image.
3. The coating compensation system based on visual coating quality inspection data according to claim 2, characterized in that, The process of correcting the highlight and dark areas within a grayscale image to obtain the corresponding corrected grayscale image includes: Obtain the mask edges of the highlighted area and the normal area, as well as the pixel values inside the highlighted area, and then obtain the pixel values to be corrected at each position inside the highlighted area; The obtained pixel values to be corrected are filled into the corresponding positions inside the highlight area, thereby completing the correction of the highlight area; Based on the pixel values at each location in the dark area and the average pixel values of the local windows at each location, the enhanced pixel values at each location in the dark area are obtained. The corresponding positions in the dark area are filled with the obtained enhanced pixel values, thereby completing the correction of the dark area.
4. The coating compensation system based on visual coating quality inspection data according to claim 3, characterized in that, The process of identifying the common feature regions of the corrected grayscale images corresponding to the captured photos from three image acquisition terminals, and fusing the obtained corrected grayscale images based on the obtained common feature regions to obtain the corresponding workpiece coating fused image includes: The edge regions of the workpiece within the corrected grayscale image are marked, and key features are extracted from the marked edge regions; the key features include the center point, convex corner, and concave corner of the workpiece edge region; The obtained key features are matched with the key features corresponding to another image acquisition terminal, and the same key features are determined based on the matching results. Based on the same key features, the common feature regions of each corrected grayscale image are determined. Based on the determined common feature regions, the corrected grayscale images corresponding to different image acquisition terminals are fused to obtain the corresponding workpiece coating fused image.
5. The coating compensation system based on visual coating quality inspection data according to claim 4, characterized in that, The process by which the feature recognition module extracts features from the fused image of the workpiece coating and calibrates the coating compensation area includes: Select a pixel threshold range, match the pixel values at each position of the workpiece coating fusion image with the selected pixel threshold range, and complete the binarization process of the workpiece coating fusion image based on the matching results to obtain the workpiece binarized image. Abnormal regions in the binarized image of the workpiece are marked, and noise is filtered out from the marked abnormal regions. A planar coordinate system is constructed for the binarized image of the workpiece, and the gradient values of the abnormal regions are obtained; A defect type reference table is set up, which includes defect types, gradient value ranges corresponding to each defect type, and corresponding compensation feasibility. The compensation feasibility includes compensateable defects and non-compensable defects. The gradient values of each abnormal region are matched with the gradient value ranges corresponding to each defect type in the defect type reference table to determine the defect type of the abnormal region and the corresponding compensation feasibility, thereby determining the corresponding coating compensation area.
6. The coating compensation system based on visual coating quality inspection data according to claim 5, characterized in that, The process by which the coating compensation module generates a corresponding coating compensation strategy based on the infrared scanning data of the coating compensation area includes: The coating compensation module is equipped with an infrared scanning unit, which marks the coating compensation area as the main compensation area. The main compensation area is scanned by the laser scanning unit, and the infrared scanning data of the main compensation area is obtained based on the scanning results. Based on the obtained infrared scanning data, the depth difference at each location within the main compensation area is obtained; Obtain the minimum value of the depth difference in the main compensation area, and obtain the required coating compensation amount at the corresponding location; Starting from this position, the coating amount of the coating compensation unit is set, and the coating compensation of the main compensation area is performed according to the set coating amount. After the coating compensation of the main compensation area is completed, the main compensation area after coating compensation is scanned again by the laser scanning unit. Then the above process is repeated until there is no depth difference in the main compensation area. A secondary compensation area is set at the edge of the main compensation area, and edge softening spraying compensation is applied to the secondary compensation area.
7. The coating compensation system based on visual coating quality inspection data according to claim 6, characterized in that, Summarize all positions at the edge of the main compensation area, draw tangents along each position, and mark the points perpendicular to the tangents and at a distance from the tangent point as the boundary points of the secondary compensation area. Repeat this process to determine the boundary points of the secondary compensation area corresponding to all positions at the edge of the main compensation area. Connect all the boundary points of the secondary compensation area in sequence to obtain the corresponding boundary lines of the secondary compensation area. The area between the boundary line of the secondary compensation area and the edge of the primary compensation area is defined as the secondary compensation area.