In Commercial environment, Gears are a very important component of almost every machine. To avoid any mechanical failure, detection of defects in gear must be detected. We designed a detection system based on machine vision to resolve such problems as low efficiency, low quality and instability of gear surface defect detection. In this paper we are using web camera for collecting images of gear products, using open CV as library for YOLO. At last, the results are fed back to the control end, and also the rejected gears are removed with the assistance of separator. The system has successfully identified defective gear. The test results show that this method can identify and eliminate defects of gears quickly and efficiently. It has reached the requirement of gear product defect detection line automation and includes a certain application value.
₹10000 (INR)
NON IEEE -2022