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Acoustic emission signal feature analysis using type-2 fuzzy logic System

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4 Author(s)
Qun Ren ; Mech. Eng. Dept., Ecole Polytech. de Montreal, Montréal, QC, Canada ; Baron, L. ; Balazinski, M. ; Jemielniak, K.

In this paper, type-2 fuzzy logic system is applied to analyse acoustic emission signal feature for tool condition monitoring in a tool micromilling process. To make the comparison and evaluation of AE signal features easier and more transparent, Type-2 fuzzy analysis is used as not only a powerful tool to model AE SFs, but also a great estimator for the ambiguities and uncertainties associated with them. Depend on the estimation of root-mean-square error (RMSE) and variations in modeling results of all signal features, reliable ones are selected and integrated into tool wear evaluation. A discussion and comparison of results is given.

Published in:

Fuzzy Information Processing Society (NAFIPS), 2010 Annual Meeting of the North American

Date of Conference:

12-14 July 2010