Component size detection system based on machine vision

By identifying and processing suspected high-reflectivity interference areas, performing edge repair and structural clustering, and combining distortion analysis and inverse compensation, the problem of dependence on light source and camera angle in traditional component inspection systems has been solved, achieving efficient and adaptive component size inspection.

CN121724969AActive Publication Date: 2026-03-24HENGYANG XINYIWEI MECHANICAL & ELECTRICAL TECH CO LTD
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Patent Information

Application Number
CN202511952038.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-05
Publication Date
2026-03-24
Estimated Expiration
2046-01-05

AI Technical Summary

Technical Problem

Traditional component size inspection systems rely on manual settings for light source arrangement and camera angle adjustment, making it difficult to adapt to changes in component position and achieve high-throughput, continuous inspection of multiple component models.

Method used

An interference area identification module is used to identify high-reflectivity suspected interference areas and invalidate responses. Linear interpolation is performed through an edge repair module, and geometric vector angle analysis is performed in combination with a structure clustering module to construct a point cloud grouping structure. Distortion analysis is performed and inverse compensation is applied to achieve adaptive detection of component size.

Benefits of technology

It enables adaptive detection of components with different orientations and surface interference, improving detection efficiency and accuracy, and adapting to continuous detection of multiple component models.

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Abstract

The invention relates to the technical field of size detection, in particular to a component size detection system based on machine vision, which comprises an interference area identification module, an edge repair module, a structure clustering module, a distortion analysis module and an attitude restoration module. According to the method, the gray level change trend of each pixel and the adjacent points in the image is obtained, the high-reflection suspected interference area is identified, the edge response cancellation processing is executed, and linear interpolation compensation is carried out by combining the effective edge response values of the adjacent areas; after a continuous contour trend is constructed, clustering and sub-grouping division are carried out according to an included angle difference trend between contour geometric vectors, a three-axis direction response linear array variation amplitude is extracted to construct a distortion curvature mapping table, existence of non-equal-interval deformation is judged, reverse angle compensation is applied, and a three-axis intersection point convergence process is completed through a nonlinear optimization algorithm; and according to the three-dimensional coordinates, calculating a geometric dimension and outputting a detection result, thereby realizing self-adaptive detection of different postures and surface interference component dimensions.
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