Multi source information fusion self-updating Bayesian network weld seam recognition system

This article proposes a pipeline weld defect detection system based on multi detection information fusion, aiming to improve detection accuracy. By preprocessing and assigning confidence values to weld defect data, applying multi-source fusion Bayesian algorithm to improve detection accuracy, and optimizing recognition accuracy through self-updating Bayesian loop. The experimental results show that the system can efficiently and accurately detect and classify weld defects, with real-time and scalability, suitable for pipeline weld defect detection, and support engineering quality management.