Sealing ring surface defect detection method based on machine vision

Abstract

The invention discloses a sealing ring surface defect detection method based on machine vision. The sealing ring surface defect detection method comprises the following steps: firstly, acquiring images of the surface of a sealing ring, and performing self-adaptive median filtering treatment on the acquired images; subsequently, calculating a gray level gradient and a vertical gradient of the images, and extracting gray bevel structures in the images according to the gray level gradient and the vertical gradient; partitioning different bevel characteristic point neighborhoods, and calculating a gray level mean of the partitioned neighborhoods; finally, by taking functions for describing the gray level difference degree of the partitioned neighborhoods as defect judgment principles, screening out defect outline points, and detecting the defects of the surface of the sealing ring. According to the forming reason of the defects of the surface of the sealing ring, inherent differences of defect outlines and appearance outline of the sealing ring can be analyzed and verified on the images, various types of defects, including recesses, rill marks, impurities, trimming and over-cutting defects, on the surface of the sealing ring can be detected, and the method has the advantages of high defect detection accuracy, good algorithm robustness and the like.

Description

technical field [0001] The invention belongs to the field of machine vision and digital image processing, and in particular relates to a method for detecting surface defects of a sealing ring based on machine vision. Background technique [0002] The spacecraft sealing system has strict quality requirements for the sealing ring used, and the integrity of its surface directly determines the performance and life of the sealing system, which in turn affects the reliability of the spacecraft in orbit. As the most widely used sealing element, the surface quality inspection of O-shaped rubber sealing ring (O-ring for short) mainly includes flow marks, lack of glue, concave and convex defects, excessive trimming, combined flash, etc. O-ring surface quality control, at present, mostly adopts visual inspection method, and checks with tool microscope or projector after problems are found. This detection method has low efficiency, low precision, and low reliability. [0003] At presen...

AI Technical Summary

Problems solved by technology

The method based on shape and geometric feature extraction (including area, length, etc.) can effectively classify images, so as to determine whether the measured object has defects and the type of defects, but it is difficult to deal with complex sealing rings with uneven imaging such as highlights and textures There are limitations when surface images

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