Research on defect detection method for thin-walled parts based on point cloud data processing

External impacts for Thin walled components can cause surface depressions and result in serious consequences. In order to detect these depressions , this article performs point cloud filtering and simplification prepossessing on the obtained defect point cloud, and uses the defective point cloud to fit a standard point cloud model; We used a point cloud feature description algorithm based on Fast Point Feature Histogram (FPFH) and the Nearest Point Iteration (ICP) algorithm to perform coarse and fine registration on two point clouds. Finally, we calculated the Euclidean distanceto defect the registered point clouds.