Workpiece apparent defect detection method based on machine vision

Abstract

The invention discloses a workpiece apparent defect detection method based on machine vision. Firstly, a visual system is used for guiding a robot, the pose of a target workpiece is precisely positioned according to a template matching algorithm based on a gray value, and then workpiece apparent defect detection is carried out and comprises the steps that firstly, a workpiece image is acquired and pretreated through median filtering; secondly, the target workpiece is divided through a global threshold value, and workpiece pose correction is carried out; thirdly, burr interference of the edge of the workpiece is removed through mathematical morphology open operation; fourthly, notches, material sticking, cracking, indentation, needle eyes, scratches and foaming apparent defects are detected. The method solves the problems that the artificial detection speed is slow, the efficiency is low and precision is poor; the problems that according to current vision detection, defect types are singular, the imaging quality is poor, and the false drop rate is high are solved, and the automation degree of precise workpiece production and product quality are improved.

Description

technical field [0001] The invention belongs to the field of automatic detection, in particular to a method for detecting workpiece appearance defects based on machine vision. Background technique [0002] The main production process of metal workpieces is machining, stamping, precision casting, powder metallurgy, metal injection molding, dimensional inspection, appearance defect inspection, etc. Affected by the manufacturing process throughout the production process, the size and appearance of the workpiece will be unqualified to a certain extent. Among them, appearance defects mainly include: gaps, sticky materials, cracks, indentations, pinholes, scratches and blisters, etc. If workpieces with appearance quality defects flow into the next production process, the assembly will be blocked and deformed, which will affect the quality of the assembled parts. potential economic losses and reputational risks. [0003] Traditional appearance defect inspection methods include m...

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Problems solved by technology

[0005] At present, the main methods of visual detection of workpiece appearance defects: (1) The automatic detection of metal workpiece surface defects is realized through genetic algorithm and visual image processing morphology. The bubble defect detection effect is poor; (2) the existence of product defects is judged by using the image grayscale feature and the abnormal change of the grayscale value, but due to the strong reflective characteristics of the metal surface, the system has a high false detection rate

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