Weld seam detection, finding and setting of process parameters for varying weld gap by the utilization of laser and vision sensor in robotic arc welding

The prime objective of the paper is to obtain maximum weld seam positional accuracy and weld quality with varying weld gap values over weld cycles in robotic arc welding. At first vision sensor has been used to obtain the seam positions, so that there is no need to teach the robot manually. For repeatable environment or for similar designed weld path, there is no need to check the weld seam positions for achieving higher productivity. The weld seam can then be found by laser sensor and if there is any error any positioning, it is then notified to robot controller to move the robot end effector to the actual position. In the second part the paper, the output data of the laser sensor in terms of variation of weld gap has been used to adjust of welding parameters at their optimal values by the application of Fuzzy logic and NSGA-II algorithm to achieve maximum weld quality. MOTOMAN MA1440A arc welding robot system has been used for experimental investigation of the proposed approach. The application of utilization of sensors has been extended by automatic detection and adjustment of robot position deviations and weld gap measurement for repetitive working environment.