A point cloud preprocessing method for complicated thin-walled ring parts with irregular section

Metallic W-ring is a typically complicated thin-walled ring part with irregular section (CTWRPIC). However, there is a lack of effective measurement methods to inspect its geometric quality in the forming process, which leads to the failure of finding the forming defects in time. Due to the smooth metal surface, complex section shape, small section size and annular closed overall structure, point cloud of the section profile obtained by the line laser scanners has serious noise, outliers and missing. To this problem, this article proposes a point cloud preprocessing method for CTWRPIC. In this method, historical measurement data based outliers statistics, initial-fine rigid registration and non-rigid registration of CAD model are introduced. Firstly, the optimal alignment of point cloud from the CAD model and measurement point cloud is realized by initial-fine rigid registration. Secondly, the point cloud of CAD model is transformed by non-rigid registration to approximate the measurement profile points, the transformed point cloud of CAD model is considered as the real profile. Thirdly, based on the transformed point cloud of CAD model and distance threshold, the adaptive removal of outliers and repair of missing are realized. Finally, the correction of profile point cloud noise is completed by combining the Alpha Shapes algorithm and the proposed repair method. Based on the proposed preprocessing method and a measurement platform equipped with line laser scanners, an on-machine measurement method for metallic W-ring is proposed, and experimental results demonstrate the advantage of the proposed method. Compared with the destructive inspection method, the mean value, standard deviation and root mean square of the distance deviation of the preprocessed point cloud are all within 11 μm.