Research on Burrs Detection of Parts Surface Based on Threshold Segmentation

Abstract:

Mental cutting process, a widespread process in the machining, which can produce the maximum number of burrs. Burr detection and deburring are crucially important to safe reliability of parts. In order to avoid the effects of subjective factors effectively, and improve the production efficiency and production automation, we introduced the machine vision technique. According to the universal burrs produced in the cutting process, this paper principally studied the image segmentation, burrs feature extraction, the improvement of adaptability based on digital image processing. The authors conclude that the algorithm applied in this paper can detect the burrs information effectively, laid a solid foundation for automatic polishing, with the certain practical value.

• Periodical: Applied Mechanics and Materials (Volume 618)
• Pages: 453-457
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.618.453
• Online since: August 2014
• Authors: Yi Zhang*, Xiao Rong Chen, Hao Lin Li, Fu Sheng Tan, Jun Fan Yan
• Keywords: Burrs Detection, HALCON, Image Segment, Machine Vision, Otsu

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