Large-size sprocket repairing based on robotic GMAW additive manufacturing

Abstract

The variable and irregular surface damage of large-size sprockets has led to many challenges in the robotic GMAW-based automatic repair, which is a problem that has not been solved well. In this paper, a highly adaptive method based on robotic GMAW additive manufacturing was developed to repair the large-size sprocket with high quality. Key technologies including 3d rebuilding of damage surface and automatic robot deposition path planning have been researched. The model of damaged sprocket surface was obtained by point cloud registration algorithm including improved Iterative Closest Point (ICP) and Boolean subtraction operations. A highly adaptive slicing and path planning method for repairing sprockets with variable and irregular surface damage was proposed. Deposition parameters were obtained through experiments and a database with neural networks. The robot repairing process was simulated by 3D animation before executing the robot codes. The developed robot GMAW repairing system has integrated 3D scan modeling, slicing, path planning, parameters planning, and 3D animation simulation. The validation experiment results of repairing the damaged sprockets showed that the developed system has strong adaptability and high efficiency, and the repair accuracy met the actual requirements.