Research on Surface Defect Detection Technology of Flywheel Disc Semi-Finished Products Based on Deep Learning

In order to avoid the disadvantages of traditional methods such as low detection efficiency and poor detection quality, this paper designs and develops an intelligent detection system based on Faster R-CNN algorithm for the problem of detecting surface defects on the flywheel disc semi-finished products. A new network based on the ResNet50 network can better catch and describe the surface defects. Based on the k-means++ clustering analysis algorithm, the anchor generation rules are optimized. The experimental results show that the average accuracy of the optimized algorithm is improved. And the detection accuracy of small defects has been greatly improved. The feasibility and effectiveness of the optimized algorithm are verified.