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

Abstract

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.