Machine vision,as an important method to replace manual detection of wheel hub surface defects,is currently the main research direction in this field.Therefore,a summary and analysis of the research status of surface defect detection technology for automotive hubs is conducted.Firstly,starting with the categories of wheel surface defects and manual detection process,the requirements and difficulties of machine vision-based wheel surface defect detection technology are expounded.Then,the development of intelligent detection algorithms based on machine vision is analyzed,including the application of traditional machine vision methods in defect image preprocessing,defect location and feature extraction,defect classification and recognition,also including the application of deep learning methods such as convolutional neural networks(CNN)in defect detection,segmentation,and other applications.Finally,the existing hub type recognition device,hub defect X-ray image acquisition device,hub surface defect image acquisition device are introduced.On the basis of analyzing the limitations and key technical issues that need to be solved in practical applications of current machine vision based intelligent detection devices,three kinds of intelligent detection experimental device design schemes are proposed.It provides theoretical and technical support for the development and performance improvement of automatic rapid detection device.
国家科技期刊平台
NSTL
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