A battery coating defect detection method, device, electronic equipment and storage medium

Abstract

The invention discloses a battery glue coating defect detection method, device, electronic equipment and storage medium, wherein the method includes the following steps: acquiring a sampling point cloud of a glue coating cross section to be tested to form a sampling point set; acquiring The reference point clouds in several glued cross-sections of the glued cross-section are used to form a number of standard point sets, and a standard template is composed of several standard point sets; the distance between the glued cross-section to be tested and the standard template is calculated based on the dynamic time warping algorithm. According to the similarity information, it is judged whether there is a coating defect in the glued cross-section to be tested; the method uses the dynamic time warping algorithm to calculate and obtain the collection point cloud of the glued cross-section to be tested and the reference point of the adjacent glued cross-section The similarity information of the cloud, based on the similarity information, quickly screens to determine the existence of glue coating defects. This detection method has high efficiency and high precision, and does not rely on specific shapes, values, materials, environments, and samples for analysis, and has a wide range of applicability wide features.

Description

technical field [0001] The present application relates to the technical field of battery detection, and in particular, to a method, device, electronic equipment and storage medium for detecting battery coating defects. Background technique [0002] In battery gluing and testing processes such as mobile phones, battery gluing is an extremely important part of battery production, ensuring accurate and even distribution of adhesives and sealants, which helps to extend the service life of batteries. [0003] Common defects in battery glue coating include: glue overflow, glue holes, and unsaturated glue filling. Timely feedback through glue coating defect detection technology can effectively improve the accuracy of glue coating defect detection and improve the efficiency of inspection quality. [0004] Existing glue coating defect detection technology generally adopts image processing combined with manual interpretation. Manual interpretation is relatively subjective and unstable...

AI Technical Summary

Problems solved by technology

[0004] Existing glue coating defect detection technology generally adopts image processing combined with manual interpretation. Manual interpretation is relatively subjective and unstable, with a high false detection rate, and the image processing scheme is easily affected by external influences such as ambient light intensity, color, and glue body color. , resulting in unstable detection results

[0005] Therefore, there are schemes on the market that use laser point cloud to process from cross section, but the existing scheme based on laser point cloud to judge from cross section has many redundant judgments and calculations in the judgment process, and it is necessary to obtain height and area through calculation , density and other data, the calculation process is cumbersome

[0006] For the above problems, there is no effective technical solution

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