3D measuring and segmentation method for hot heavy forging

Abstract

Non-contact, three-dimensional (3D) measurements of hot heavy forgings (HHFs) are desirable for permitting real-time process control, whereas most current methods are usually inconvenient or invalid due to the difficulty in dealing with the hot heavy forgings. This paper presents a new measuring and combined segmentation approach that employs a two-dimensional (2D) laser radar with additional rotation driven by the servomotor that scans the forgings to acquire a massive 3D point cloud dataset. From this dataset, the desired forging part is roughly distinguished from the background based on the angle and distance continuity constraints, and then refined by the curvature-based border extraction method and further segmented by the hierarchical clustering analysis method. Finally, the feature points are extracted based on the normal vector variation and fitted to convey the 3D information. This novel method has been verified by experiments both in the laboratory and the forging workshop for hot heavy forging pieces, with a dimension error of less than 2%. These results indicate that the proposed approach is more practical and convenient than current methods for real-time, on-site measurements of HHFs.