Seam tracking and weld penetration control are two fundamental issues in automated welding. Although the seam tracking technique has matured, the latter still remains a unique unsolved problem. It was found that the full penetration status during GTA welding can be determined with sufficient accuracy using the sag depression. To achieve a new full penetration sensing technique, a structured-light 3D vision system is developed to extract the sag geometry behind the pool. The laser stripe, which is the intersection of the structured-light and weldment, is thinned and then used to acquire the sag geometry. To reduce possible control delay, a small distance is selected between the pool rear and laser stripe. An adaptive dynamic search for rapid thinning of the stripe and the maximum principle of slope difference for unbiased recognition of sag border were proposed to develop an effective real-time image processing algorithm for sag geometry acquisition. Experiments have shown that the proposed sensor and image algorithm can provide reliable feedback information of sag geometry for the full penetration control system.
Multiprocessor 3D vision system for pick and place
