Real-Time Industrial Automated Video Analytics System for Welding Defect Detection

The control of quality is an obligatory stage of any welding work which makes problem of timely detection of welding defects is important for industry nowadays. Through digitisation it possible to solve this problem more efficiently and eliminate the human factor. This paper presents a real-time industrial automated video analytics system for weld defect detection. The system uses deep learning to analyze video images and detect weld defects in real-time. Experiments showed that the system can effectively detect weld defects with high accuracy and speed. A safety and trustworthiness analysis of the system showed that it can be reliable and safe for use in industrial manufacturing. The proposed solution has several key advantages for the industry: it allows for real-time data processinga and requires low computing power, making it an energy-efficient and cost-effective solution.