面向微束等离子选区熔化的在线检测系统OA北大核心CSTPCD

In order to solve the problem of shape control in the process of micro-beam plasma selective melting,a set of on-line detection system for microbeam selective melting was developed.The system takes each layer of formed metal as the research object,based on the principle of deep learning target detection,detects defects on the metal forming surface image,and controls the start and stop of the equipment according to the detection results to ensure that the forming quality of each layer meets the requirements.At the same time,through the cooperation of the binocular camera and the line laser,the three-dimensional reconstruction of the formed surface topography is carried out by means of linear array scanning,and displayed on the self-developed visualization software,realizing the detection scheme combining defect detection and three-dimensional reconstruction.The experimental results show that the system can quickly and accurately detect the defects generated in the forming process,with strong real-time performance and low missed detection rate,and the results are fed back to the system in time,realizing the active and effective control of the shape.