Research On Inside Hole Defect Detection System Of Automobile Insurance Box Based On Machine Vision

Machine vision is widely used in the field of industrial detection,and its detection accuracy and efficiency have been improved qualitatively compared with manual detection.In this paper,aiming at the need of industrial inspection of the inner hole defect of automobile insurance box,the defect detection system of the inner hole of automobile insurance box based on machine vision is studied.Firstly,according to the inspection requirement of automobile insurance box,the lenses,camera and light source of machine vision imaging system are theoretically analyzed and calculated,and the supporting mechanism of the imaging system is designed to improve the imaging quality of the system.Secondly,Aiming at the problem that the automobile insurance box is easy to be mischecked in actual inspection,this paper analyses the causes of the problem from two aspects: the thermal expansion and cold contraction of the workpiece and the manufacture of the modules,and puts forward the method of classifying and re-testing the workpieces produced by different modules.Aiming at the problem that the same defect is detected repeatedly during the detection,a self-checking method is designed.Compared with the prior insurance box defect detection system,the mistaken detection rate of the system designed in this paper is reduced.Thirdly,aiming at the problem that the matching effect of the inner hole image of insurance box is not good in the process of detection,this paper proposes an image segmentation strategy based on the regional image features,uses the regional registration strategy based on location factor to restrict the matching,and designs a template filtering method.The experimental results show that the matching accuracy of the proposed method is 8% higher than that of the existing method.Then,aiming at the problem that the matching time is too long at present,this paper studies the matching method based on bilateral projection histogram in algorithm,GPU acceleration technology in hardware equipment to optimize the matching step in real time.The experimental results show that the time-consuming of the proposed method is 70% less than that of the existing methods.Finally,aiming at the problem of error detection in actual detection process,an algorithm for fault self-diagnosis of detection system is studied to reduce the workload of manual troubleshooting.This paper develops a defect detection system of the insurance box,and carries out an experimental study on the system.The experimental results show that the accuracy of the system for the detection of the inner hole of the insurance box is at least 13% higher than that of the existing system.