Research on defect detection system for magnetic ring materials in electric motors based on ResNet and Canny operator edge circle fitting method

This paper proposes a machine vision defect detection algorithm based on ResNet and Canny operator edge approximation to address the quality monitoring issues in the manufacturing process of motor magnetic materials. Based on this detection method, an automated device system for detecting motor magnetic ring defects is constructed. This article uses the Canny operator of the maximum connected curve to obtain the contour of the original sample image. Based on the coordinate information of the contour points, the image is divided into several parts to reduce the dimensionality of the image samples. The obtained small image information is used as input to ResNet to achieve the detection of incomplete surface loops, pits, missing corners, cracks, etc. The results show that the prediction accuracy is 96.70%, and the average accuracy mAP is 92.92%. The missed kill rates in the training and prediction models are 2.22% and 4.44%, respectively, which are lower than the overall kill rate and meet the production sorting needs of enterprises.