Structure identification of fuzzy model
Fuzzy Sets and Systems
Continuous and discrete wavelet transforms
SIAM Review
Identification of non-linear system structure and parameters using regime decomposition
Automatica (Journal of IFAC)
Type 2 fuzzy sets: an appraisal of theory and applications
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Subtractive clustering based modeling of job sequencing with parametric search
Fuzzy Sets and Systems - Data analysis
Condition Monitoring and Control for Intelligent Manufacturing (Springer Series in Advanced Manufacturing)
Tool Condition Monitoring Using the TSK Fuzzy Approach Based on Subtractive Clustering Method
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Uncertainty prediction for tool wear condition using type-2 TSK fuzzy approach
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
TSK fuzzy modeling for tool wear condition in turning processes: An experimental study
Engineering Applications of Artificial Intelligence
Application of the wavelet transform to acoustic emission signalsprocessing
IEEE Transactions on Signal Processing
Type-2 FLCs: A New Generation of Fuzzy Controllers
IEEE Computational Intelligence Magazine
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
Type-2 fuzzy tool condition monitoring system based on acoustic emission in micromilling
Information Sciences: an International Journal
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This paper presents an application of type-2 fuzzy logic on acoustic emission (AE) signal modeling in precision manufacturing. Type-2 fuzzy modeling is used to identify the AE signal in precision machining. It provides a simple way to arrive at a definite conclusion without understanding the exact physics of the machining process. Moreover, the interval set of the output from the type-2 fuzzy approach assesses the information about the uncertainty in the AE signal, which can be of great value for investigation of tool wear conditions. Experiments show that the development of the AE signal uncertainty trend corresponds to that of the tool wear. Information from the AE uncertainty scheme can be used to make decisions or investigate the tool condition so as to enhance the reliability of tool wear.