Edge defect detection method

Abstract

The invention belongs to the technical field of industrial detection, and particularly relates to an edge defect detection method, which comprises the following steps of: acquiring image information of an edge area of an object to be detected, and calculating and obtaining edge contour point information of the object to be detected according to the acquired image information; detecting and recording suspicious defect points in the edge contour points to form a suspicious defect point set; carrying out clustering grouping on the recorded suspicious defect point set, carrying out linear discrimination on the obtained groups, and generating fitting lines; calculating the distance between each suspicious defect point and the fitting line, judging whether the distance is greater than a preset threshold value or not, and if the distance is greater than the threshold value, determining the suspicious defect point as an edge defect point to obtain a detection result. The edge defect detectionmethod can perform non-contact type automatic detection on the workpiece, avoids damage caused by manual detection, improves the detection precision and efficiency, can also detect the edge of a non-specific shape, and improves the universality.

Description

technical field [0001] The invention belongs to the technical field of industrial detection, and in particular relates to a detection method for edge defects. Background technique [0002] In industrial production and manufacturing, due to the precision of production equipment or human operation, it is unavoidable that there are depressions or burrs on the edge of the produced workpiece. The workpiece edge is an important feature of workpiece production, which directly affects the quality of the workpiece. In order to ensure the production quality of the workpiece, it is often necessary to detect the edge defects of the workpiece to ensure the quality of the workpiece. [0003] At present, the detection method of workpiece edge defects in the industry is generally through manual detection, relying on the naked eye to find the edge defect points of the workpiece, but this method is likely to cause damage to the recessed area or the burr is worn off during detection. In additi...

AI Technical Summary

Problems solved by technology

[0003] At present, the detection method of workpiece edge defects in the industry is generally through manual detection, relying on the naked eye to find the edge defect points of the workpiece, but this method is likely to cause damage to the recessed area or the burr is worn off during detection. In addition, when faced with For workpieces with irregular shapes or a large number of defects, especially on some die-casting parts, the size, shape and position of edge defects have a certain degree of randomness, which leads to slow manual inspection, high labor intensity, poor reliability, Defects such as high missed detection rate, and manual detection can easily cause visual fatigue, affect the detection judgment, and cannot guarantee the detection speed and accuracy. Although there have been some solutions for edge detection using machines in recent years, most of them are only for Specific products or workpieces with specific shapes are detected, such as mobile phone screens, mobile phone casings, etc., which are all linear, circular or arc-shaped edges, and there are limitations in edge detection

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