Machine Vision-Based Chamfer Detection for Metal Parts
This paper introduces a detection system specifically designed for chamfering in metal holes, aimed at achieving precise detection of the chamfers.Chamfering, as a process of beveling the edges or corners of metal parts, plays a crucial role in the subsequent machining and assembly stages.Through multiple experimental validations, this paper employs an industrial camera with a telecentric lens to capture images of the metal chamfers, achieving optimal results.This paper utilizes computer vision techniques to accurately identify the location of the chamfers and delineate their dimensions.A comprehensive analysis of the chamfer radius effectively determines the presence of defects.
Authors
- Junjin Chen
- Ce Bian (ORCID: https://orcid.org/0000-0002-5320-4328)
- Shuo Han (ORCID: https://orcid.org/0000-0003-2033-9004)
- Yuanhang Kong (ORCID: https://orcid.org/0009-0002-6497-881X)
- Yanzi Kong (ORCID: https://orcid.org/0000-0003-0780-6966)
- Mengfan Zhang (ORCID: https://orcid.org/0000-0002-8655-5247)
- Kaiming Guo (ORCID: https://orcid.org/0000-0002-4749-3864)
Institutions
- Tianjin University of Science and Technology (CN)
- Tianjin Tianhe Hospital (CN)
- Semiconductor Manufacturing International (China) (CN)
- Tianjin Medical University (CN)
Publication Details
- Journal
- Proceedings of International Conference on Artificial Life and Robotics
- Published
- 2025-02-13
- DOI
- https://doi.org/10.5954/icarob.2025.os9-4
- Primary Topic
- Image and Object Detection Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00