Hardware defect identification method, system and storage medium

Abstract

The invention discloses a hardware defect identification method, system and storage medium. The method includes the following steps: performing scratch detection according to the image information of the hardware; performing subtle defect detection according to the image information of the hardware; extracting the defect according to the image information of the hardware The point cloud data of the defect area; after the detection operation is confirmed, according to the point cloud data of the defect area, curve fitting is performed on the spatial position points of the defect area; according to the fitted curve, the time-optimal processing path is generated; The optimal processing path controls the robot for automatic grinding. The invention solves the problems existing in the manual detection mode in the prior art, improves the detection efficiency and reduces detection errors, and can be widely used in the technical field of metal grinding.

Description

Technical field[0001]The present invention relates to the field of metal grinding techniques, in particular a defective recognition method, system, and storage medium of the hardware member.Background technique[0002]The surface defect of metal parts is mainly caused by metal molding to various processing processes, such as scratch defects, uneven defects, and stains such as stains.[0003]When a plurality of defects (i.e., multiple grinding areas) in the surface of the metal part, the defect position is dispersed, the process of grinding which area of ​​the robot has directly determined the overall processing efficiency and the degree of intelligence of the grinding system.[0004]The inspection of the surface defects of the hardware is a very critical process in many enterprises production. In a large number of product production processes, check the surface of the surface is defective after processing, such as computer panels, auto parts and molds. Different kinds of metal parts in th...

AI Technical Summary

Problems solved by technology

[0005] At present, the hardware surface inspection process mainly relies on the naked eye observation, which is affected by subjective factors, and there are problems such as limited accuracy and unstable results. Moreover, the labor shortage that has been increasing in recent years is also constantly affecting the labor cost of production.

Although visual inspection by human eyes has its own advantages, it is very suitable for situations where there are many changes in product varieties and defect types. However, visual inspection by human eyes is a repetitive, boring and tiring work.

Therefore, the characteristics of human eye defect inspection are slow detection speed, unstable effect and very subjective judgment of detection standards.

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