Research on welding trajectory tracking against strong interference based on laser vision and model predictive control

Under interference environments such as strong arc light, splashing, smoke and dust, and strong noise, the accuracy and stability of weld trajectory tracking control are important guarantees for achieving high-quality welding. After preprocessing the weld seam images obtained from laser vision, curve fitting is used to connect them into lines and extract the center feature points of the light strip during the welding process. The feature point coordinates are converted and the feature point line is used as the reference trajectory of the weld seam. In order to solve the planning problems encountered in the welding seam tracking process, the optimal transverse and longitudinal movement speed of the welding gun head is obtained based on the predictive control model. The obtained parameters are used as the input of the welding system and transferred to the execution mechanism to achieve more accurate tracking of the welding seam trajectory.