Research on Brake Drum Surface Defect Detection System Based on Machine Vision Technology

This paper focuses on the development of an efficient and accurate brake drum surface defect detection system to meet the growing demands for brake safety performance in the manufacturing industry. The system analyzes common defect types on brake drum surfaces, such as chips and cracks, and designs a comprehensive detection scheme. In terms of hardware architecture, it integrates high-resolution image acquisition equipment and a customized lighting system to ensure clear and comprehensive images of the brake drum surface under different lighting conditions. At the software level, the system implements image preprocessing steps, including noise filtering and contrast enhancement, to optimize image quality. Subsequently, advanced feature extraction algorithms are used to precisely locate and analyze the characteristic information of potential defects. Ultimately, the system achieves the identification of brake drum surface defects. Experimental results show that the system not only effectively distinguishes between different types of surface defects but also exhibits significant advantages in detection speed and accuracy, significantly enhancing the efficiency of quality control on brake drum production lines. Compared with traditional manual detection methods, this system significantly reduces the rates of missed and false detections while alleviating the human workload, providing strong support for the intelligent upgrade of the brake manufacturer industry.