Method for detecting irregular defect of industrial product

Abstract

A method for detecting irregular defects of industrial products comprises the following steps: step 1, image enhancement processing, specifically comprising histogram equalization and histogram matching; step 2, constructing a network model; and step 3, setting relevant parameters of the network model, specifically including setting of a default box, a default box matching mode and composition ofa loss function. According to the invention, image enhancement processing is carried out on a collected sample image, so that defects are more obvious. Then, on the basis of a convolutional neural network CNN, a defect detection network model is constructed in combination with the SSD target recognition model, and model parameters are reasonably designed, so that the detection problem of irregulardefects can be effectively solved.

Description

technical field [0001] The invention relates to a method for detecting irregular defects of industrial products. [0002] technical background [0003] In industrial production, the quality problems of industrial products are mainly manifested in problems such as production defects, assembly defects, various surface defects, and products that do not match the design. These quality problems are affected by many factors, such as production equipment, operators, and processing technology. Wait. Among them, the surface defect of the product is the main manifestation of the quality defect of the industrial product. The traditional surface defect detection method is manual visual detection, that is, human visual recognition in a specific environment, but this detection method has many disadvantages, such as high labor intensity, low work efficiency, high cost, and easy Affected by the quality and experience of the inspectors, etc. [0004] Industrialized large-scale production h...

AI Technical Summary

Problems solved by technology

However, it is unavoidable that machine vision inspection technology still has some defects, such as: the detection effect of products with irregular defects is not good; it is limited by the computing power of the computer, which requires high computing power; it has real-time problems

In short, the traditional manual inspection method and some visual inspection technologies based on machine vision inspection have shortcomings, and cannot meet the needs of the industrial product inspection market. There is an urgent need for a detection method that meets market demand.

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