Defect detection of gear parts in virtual manufacturing
Abstract Gears play an important role in virtual manufacturing systems for digital twins; however, the image of gear tooth defects is difficult to acquire owing to its non-convex shape. In this study, a deep learning network is proposed to detect gear defects based on their point cloud representatio...
Main Authors: | Zhenxing Xu, Aizeng Wang, Fei Hou, Gang Zhao |
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Format: | Article |
Language: | English |
Published: |
SpringerOpen
2023-03-01
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Series: | Visual Computing for Industry, Biomedicine, and Art |
Subjects: | |
Online Access: | https://doi.org/10.1186/s42492-023-00133-8 |
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