A Vision-Based Self-Tuning Fuzzy Controller for Fillet Weld Seam Tracking

In this paper, an intelligent seam-tracking system is developed for fillet weld workpiece. Structured light vision is employed to detect the deviation of the welding torch. Two stripe lines are formed on the surface of the fillet weld workpiece by the structured laser light. Their intercepts are selected as the image feature, which can result in an approximately uncoupled relationship between the image feature and the movement of adjustment mechanism. A two-step feature-extraction method is designed to robustly detect the two lines in image. In order to get a favorable tracking precision in the welding process, a new self-tuning fuzzy controller is designed. Its input and output scaling factors are tuned according to its active working region. Moreover, a supervisory level is introduced into the control system to limit the output pulses in order to guarantee steady and safe tracking. Finally, experiments are well conducted to verify the performance of the proposed system and methods.