Research on Burrs Detection of Parts Surface Based on Threshold Segmentation

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...

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Veröffentlicht in:Applied Mechanics and Materials 2014-08, Vol.618 (Materials, Machines and Development of Technologies for Industrial Production), p.453-457
Hauptverfasser: Yan, Jun Fan, Li, Hao Lin, Tan, Fu Sheng, Zhang, Yi, Chen, Xiao Rong
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Sprache:eng
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Zusammenfassung: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.
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.618.453