Geometric defects identification and deviation compensation in laser deposition manufacturing

•A compensation methodology using in-situ point cloud is developed and validated.•The automated defects detection, contour extraction and tool path generation.•The methodology can be used to identify melting concave and edge collapse.•The methodology is significant for large-scale part and compensating defects. Geometric defect can result in a failed part and is costly in terms of time and material. Detecting and control defect is essential for apartbyadditivemanufacturing to avoid further deterioration of the part accuracy. In this paper, a defect identification and compensation method for laser deposition manufacturing(LDM) is proposed to enhance the part quality. This work investigated the use of high-speed laser profiler to collect the surface point cloud concerning a part under building, and then these data were utilized to detect the defect region according to the given deviation threshold. Statistic filter, least-square method and projection approach were employed for deviation point cloud denoising, segmentation and contour extraction. An algorithm was presented to distinguish regions which needed compensation and generated corresponding scan path based on in-situ point cloud processing. The experimental results showed that the setup successfuldetected the geometric defects of the LDM part and controlled the machine motion system to deposit the deviation region, and the resulting part was more geometrically identical to the expected 3D representation.