Applying Computer Vision in Fuses Inspection

• Main Authors: Po-Yi Li, 李柏毅
• Other Authors: 田方治
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/ym65hh

碩士 === 國立臺北科技大學 === 工業工程與管理研究所 === 97 === In the highly competitive environment, an industry should provide better performance, lower cost, and lower price products to survive and win more share of the market. The automatic manufacturing process is essential to achieve this goal. In this study, we use the fuses as the samples to inspect all the defects produced in the casting process. We proposed an approach by using statistical method to find the defects, and compared to the BP and LVQ neural networks. The results indicate that the speed and the reliability of the method we proposed are better than the other two methods. It only takes 0.24 seconds to inspect a fuse in this system. The correct rate reaches about 95.94%. This system is much faster and preciser than human and neural network inspections.