Tool wear assessment based on type-2 fuzzy uncertainty estimation on acoustic emission |
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| Affiliation: | 1. Department of Automatic Manufacturing Engineering, École de Technologie Supérieure, University of Quebec, 1100 Notre-Dame St W, Montreal, Québec H3C 1K3, Canada;2. Department of Mechanical Engineering, Polytechnique Montréal, University of Montreal, C.P. 6079, Succ. Centre-Ville, Montréal, Québec H3C 3A7, Canada;1. Université du Québec en Outaouais, 101 Saint-Jean-Bosco, Gatineau, QC J8X 3X7, Canada;2. University of Ottawa, 800 King Edward, Ottawa, ON K1N 6N5, Canada;1. Faculty of Science, University of Kragujevac, R. Domanovi?a 12, 34000 Kragujevac, Serbia;2. Mathematical Institute, Serbian Academy of Science and Arts, Kneza Mihaila 36 (P.O. Box 367), 11001 Belgrade, Serbia;1. College of Science, Guangxi University for Nationalities, Nanning, Guangxi 530006, PR China;2. Guangxi Key Laboratory of Hybrid Computational and IC Design Analysis, Nanning, Guangxi 530006, PR China;3. College of Information Science and Engineering, Guangxi University for Nationalities, Nanning, Guangxi 530006, PR China;4. College of Science, Guangxi University for Nationalities, Nanning, Guangxi 530006, PR China |
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| Abstract: | In modern manufacturing industry, developing automated tool condition monitoring system become more and more import in order to transform manufacturing systems from manually operated production machines to highly automated machining centres. This paper presents a nouvelle cutting tool wear assessment in high precision turning process using type-2 fuzzy uncertainty estimation on acoustic Emission. Without understanding the exact physics of the machining process, type-2 fuzzy logic system identifies acoustic emission signal during the process and its interval set of output assesses the uncertainty information in the signal. The experimental study shows that the development trend of uncertainty in acoustic emission signal corresponds to that of cutting tool wear. The estimation of uncertainties can be used for proving the conformance with specifications for products or auto-controlling of machine system, which has great meaning for continuously improvement in product quality, reliability and manufacturing efficiency in machining industry. |
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| Keywords: | Type-2 fuzzy logic system Subtractive clustering Precision machining Acoustic emission Tool wear Uncertainty estimation |
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