Burr Detection Using Image Processing in Milling Workpieces
| Autor: | Lidia Sánchez-González, Virginia Riego del Castillo, Manuel Castejón-Limas, Laura Fernández-Robles |
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| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Vision based Computer science business.industry Quality assessment Production cost media_common.quotation_subject Image processing 02 engineering and technology Function (mathematics) Edge (geometry) 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Quality (business) Computer vision Artificial intelligence business media_common |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030578015 SOCO |
| DOI: | 10.1007/978-3-030-57802-2_72 |
| Popis: | Manufacturing processes require to satisfy quality standards in the produced parts. In particular, the edge finishing must be burr-free, avoiding that it yields different problems such as wasting time removing them what increases the production cost and time. A burr can be noticed microscopically, but it can contain imperfections or evidence of poor piece design. In order to detect automatically this imperfections and to evaluate the quality of the edge finishing, this paper proposes a complete vision based method using image processing and linear regression. With the calculated function, the slope is isolated and compared to obtain quality assessment thresholds. Results validate the good performance of the proposed method to differenciate three types of burrs. |
| Databáze: | OpenAIRE |
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