Method for detecting defects of bearing sealing element based on vision

Abstract

The invention discloses a method for detecting defects of a bearing sealing element based on vision. The method includes the steps: obtaining a bearing sealing element image; treating the bearing sealing element image by using an image segmentation and target association method, to obtain a workpiece image of the bearing sealing element; calculating the workpiece image by using a workpiece range, to obtain an effective workpiece image of the bearing sealing element; treating the effective workpiece image by using a workpiece range comparison and direction difference judgment method, to obtain a burr defect; treating the effective workpiece image by using a histogram analysis method, to obtain a right-side workpiece image and a reverse-side workpiece image; treating the right-side workpiece image by using a color significance and rectangle feature judging method, to obtain a chromatic aberration defect; calculating the reverse-side workpiece image by using a metal range, to obtain a workpiece metal part image; and treating the workpiece metal part image by using a brightness significance and color transformation method, to obtain glue overflow and corrosion defects. The method solves the problem of on-line detection of the bearing sealing element, and improves the automation level.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of machine vision, and in particular, to a vision-based defect detection method for a bearing seal. Background technique [0002] At present, my country's bearing manufacturing industry is still dominated by traditional products, and the technical level is not high. The impact of this is that domestic bearing production is still mainly labor-intensive, with high overall output, but low technical content, low precision, The added value of the product is low, and the quality cannot be guaranteed. Although a few domestic bearing manufacturers have introduced some automatic and semi-automatic bearing manufacturing equipment from abroad, and formed the production capacity of some high-precision bearing products, the quality of products cannot be guaranteed because the detection methods are mainly manual detection and offline random inspection. , unable to meet the quality requirements of for...

AI Technical Summary

Problems solved by technology

However, the existing visual inspection system cannot be applied to the on-line detection of bearing seals. The main reasons are: 1) The pattern of bearing seals is relatively complex, with various colors, and there are front and back sides, and the area of ​​the metal area of ​​the back seal The difference is very large. 2) There are many types of defects on the bearing seals, includin...

Images