Identification and Detection of Automotive Door Panel Solder Joints based on YOLO

摘要

The identification of the solder joints of the automobile door panel is an important part of the automatic welding production line of the automobile door panel. In order to improve the efficiency of the automotive door panel welding line, an algorithm for quickly and accurately identifying and detecting the position of the solder joint is needed. This paper presents a method for identifying the solder joints of automotive door panels based on YOLO algorithm. YOLO can effectively distinguish image features by using a convolutional neural network to extract depth features, the experimental results show that the YOLO algorithm can accurately identify and detect the position of the solder joints, which indicate the effectiveness of the method. The average detection time is less than 0.2 seconds, which meets the real-time requirements of the production line.