Development and validation of a real-time vision-based automatic HDMI wire-split inspection system

In the production process of HDMI cables, manual intervention is often required, resulting in low production efficiency and time-consuming. The paper presents a real-time vision-based automatic inspection system for HDMI cables to reduce the labor requirement in the production process. The system consists of hardware and software design. Since the wires in HDMI cables are tiny objects, the hardware design includes an image capture platform with a high-resolution camera and a ring light source to acquire high-resolution and high-quality images of the wires. The software design includes a data augmentation system and an automatic HDMI wire-split inspection system. The former aims to increase the number and diversity of training samples. The latter is designed to detect the coordinate position of the wire center and the corresponding Pin-ID (pid) number and output the results to the wire-bonding machine to perform subsequent tasks. In addition, a new HDMI cable dataset is created to train and evaluate a series of existing detection network models for this study. The experimental results show that the detection accuracy of the wire center using the existing YOLOv4 detector reaches 99.9%. Furthermore, the proposed system reduces the execution time by about 38.67% compared with the traditional manual wire-split inspection operation.