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In the grinding process of friction stir weld seams, excessive grinding will cause damage to the base metal and bring significant economic losses. In this paper, the authors design a robotic system for grinding the weld seam and present a monitoring method of excessive grinding. The designed system consists of an industrial robot, a line scanner for measuring the weld seam and a force-controlled grinding tool. Since the result of the measurement of the weld seam is a point cloud, the extraction method of the weld seam point cloud based on graph-cut is proposed in this paper. The extracted features are used as prior knowledge of the monitoring algorithm. On the other hand, by combining the features from the point cloud and force-position information during the processing, a monitoring method for excessive grinding based on PSO-SVM is proposed and verified by experiments. The experiments demonstrate that the proposed method can identify excessive grinding, and the accuracy of recognition is 91.5%.

System Design and Monitoring Method of Robot Grinding for Friction Stir Weld Seam