Electric contacts inspection using machine vision

Machine vision is an excellent tool for inspecting a variety of industrial items such as textiles, printed circuit boards, electric components, labels, integrated circuits (IC), machine tools and fruits. In this paper, we propose machine vision-based inspection system for electric contact (EC), which are popularly used in switches, breakers and relays, and are important components in the electrical industry. The proposed system consists of three sub-systems, which inspect the top, side, and bottom surfaces of electric contact for different types of defects respectively. The system acquires the digital image of three views and classifies the surface defects including cracks, breaks, and scratches. For each view, this study develops different image pre-processing and feature extraction methods to enhance and detect the surface defects. The proposed system was implemented and verified using 229 samples collected from the EC production lines. Experimental results show the proposed system is effective and efficient in identifying EC defects.