Defect detection algorithm for bearing end face based on machine vision technology
                                               LUO Teng bin1, CHEN Shuo1, ZHAO Zi yang1, LIAN Qing hui2

（1.School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350116, China；2.Fujian Yongan Bearing Co., Ltd., Yongan 366000, China）

Abstract: Aiming at the problems of low efficiency and high influence of human factors in manual inspection of bearing end face defects,a method was proposed to detect the defects of bearing end surface by machine vision technology.Firstly, the image was smoothed and the edge detection was done by using the Canny operator of adaptive threshold. Secondly, the contour circle was fitted by the least square method to extract the annular area of the bearing end face.Thirdly, the optimal threshold of the ring region was calculated by Otsu algorithm, so that the threshold segmentation can be realized. Finally, the defects were detected and discriminated by extracting the characteristics of the connected domains. The experimental results indicate that the method can effectively detect the defects. The false detection rate is less than 3% and the undetected rate is less than 1%. The detection time is less than 50ms.The proposed algorithm can meet the requirements of on line inspection.
Key words: bearing; surface inspection; otsu algorithm; machine vision