Abstract
Metal cutting operations constitute a large percentage of the manufacturing activity. Cutting tool condition monitoring is certainly the important monitoring requirement of unintended machining operations. A multi-purpose intelligent tool condition monitoring technique for metal cutting process will be introduced in this paper. The knowledge based intelligent pattern recognition algorithm is mainly composed of a fuzzy feature filter and algebraic neurofuzzy networks. It can carry out the fusion of multi-sensor information to enable the proposed intelligent architecture to recognize the tool condition successfully. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Fu, P., & Hope, A. D. (2006). The application of B-bpline neurofuzzy networks for condition monitoring of metal cutting tool. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4099 LNAI, pp. 1078–1082). Springer Verlag. https://doi.org/10.1007/978-3-540-36668-3_137
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