Vision-Based Auto-Teaching for Automated PCB Depaneling
Machines for automated PCB depaneling have greatly improved the industrial production efficiency of electronic products. But the preparation for automated depaneling could be very complex and time-consuming. In this paper, we propose a novel systematic solution for this problem. Using a visionbased assistant system, called Auto-Teaching, all connection tabs that should be milled off panels are detected automatically. Highly accurate milling curves are generated with respect to the geometry of the corresponding tabs. Then they could be easily converted into CNC code which drive milling cutters later. Moreover, placement suggestions of supporting pins used to fix panels are obtained. All image analysis functions are implemented in C++ and optimized to meet the minimal hardware and time requirements. Thus the whole process of the preparation is simplified for users and the PCB manufactures can benefit from reduced idle running of machines and labor costs.
PCB depaneling vision panoramic imaging industrial image processing morphological operation thinning pruning
Wei Li Matthias Breier Til Aach
Institute of Imaging and Computer Vision, RWTH Aachen University, 52056 Aachen, Germany
国际会议
IEEE 10th International Conference on Industrial Informatics(第十届IEEE工业信息学国际学术会议 INDIN2012)
北京
英文
910-915
2012-07-25（万方平台首次上网日期，不代表论文的发表时间）