A vision inspection system for the defects of resistance spot welding based on neural network

Abstract

The appearance of spot welding reflects the quality of welding to a large extent. In this study, we developed a vision inspection system, which recognizes the defects of weld in electronic components based on neural network. First, the images of weld are acquired by color camera. Then, we extracted 15 features from the welding images that had been corrected and enhanced. Finally, we used 1800 training samples to train the neural network. And then we got a accuracy of 95.82% under 407 testing samples by the neural network classifier, which had 15 input nodes, 4 hidden nodes and 2 output nodes.