Type-2 TSK Fuzzy Filtering and Uncertainty Estimation for Acoustic Emission in Precision Manufacturing

Q. Ren, L. Baron, and M. Balazinski (Canada)


type-2 TSK fuzzy filtering, subtractive clustering, precision machining, uncertainty estimation, acoustic emission


Along with the scale of precision machining becomes finer and closer to the dimensional scale of material properties, microscopic sources become very significant and must be introduced as an important acoustic emission (AE) sources in precision manufacturing. In this paper, type-2 Takagi-Sugeno-Kang (TSK) fuzzy filtering is used to eliminate the noise components in the AE signal, which provides a simple way to arrive at a definite conclusion based upon the information obtained with the difficulty in understanding the exact physics of the machining process. The interval set of output from the type-2 fuzzy approach assesses the information of uncertainty in the AE signal, which can be of great value for investigation on tool wear condition.

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