3D measuring and segmentation method for hot heavy forging |
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| Affiliation: | 1. School of Electronics Engineering, VIT University, Vellore, Tamil Nadu 632014, India;2. School of Electrical Engineering, VIT University, Vellore, Tamil Nadu 632014, India;3. Department of Instrument Technology, Andhra University, Visakhapatnam, Andhra Pradesh 532001, India;1. S2P Ltd., Laboratory for Motor Control and Motor Behaviour, Ljubljana, Slovenia;2. University of Ljubljana, Faculty of Sport, Laboratory for Biomechanics, Ljubljana, Slovenia;3. University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Koper, Slovenia;4. University of Primorska, Andrej Marusic Institute, Department of Health Studies, Koper, Slovenia;1. Physics Department, Faculty of Science and Technology, Universitas Airlangga, Surabaya, Indonesia;2. Physics Department, Faculty of Mathematics and Science, The State University of Malang, Malang, Indonesia;1. Department of Biomedical Engineering, National Cheng Kung University, 1 University Road, Tainan City 701, Taiwan;2. Musculoskeletal Research Center, National Cheng Kung University, 1 University Road, Tainan City 701, Taiwan;3. Department of Occupational Therapy, National Cheng Kung University, 1 University Road, Tainan City 701, Taiwan;4. Department of Orthopedics, National Cheng Kung University Hospital, 138 Sheng Li Road, Tainan City 701, Taiwan;5. Medical Device Innovation Center, National Cheng Kung University, 1 University Road, Tainan City 701, Taiwan |
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| 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. |
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| Keywords: | Laser radar measurement system Point cloud segmentation Continuity constraint Equivalent curvature Cluster analysis Hot heavy forging |
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