Abstract
Abstract In this paper, to monitor single crystal diamond tool wear in ultraprecision machining process, a fuzzy pattern recognition technique was introduced. Some selected features to partition the cluster of pattern were obtained from time series AR modeling of dynamic cutting force signals. The wear on a diamond tool edge appears to be classifiable into two types, one of which is micro-chipping and the other gradual, both very small quantities to detect compared to conventional tool wear. In this regard, a fuzzy technique in pattern recognition, which considers the ambiguity in classification as well as the weakness of the cutting force variation, was used for monitoring the diamond tool wear status.
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