Design of PCB Defect Detection System Based on PyQt

Abstract

With the rapid development of electronic manufacturing industry, printed Circuit Board (PCB) is the core hub of electronic products, and its quality inspection plays a decisive role in ensuring the performance and reliability of products. In order to overcome the shortcomings of weak interactivity and low visualization of traditional PCB board defect detection methods, this study designed a highly interactive and intuitive PCB board defect detection system based on YOLOv5 with the help of PyQt toolkit. The system has a UI with complete functions and stable performance, which includes three functional modules: model selection, image input and detection result display. The system can not only accurately identify PCB short circuit, open circuit and other defects, but also accurately mark the location in a visual way on the inspection image, and enumerate the types of defects in detail, which greatly improves the readability and understandability of the inspection results. The UI designed in this study provides an intuitive and efficient operation platform for PCB board defect detection work, which is expected to promote the innovation and development of quality detection technology in the electronic manufacturing industry.