This paper introduces a fuzzy pattern recognition technique for monitoring single crystal diamond tool wear in the ultraprecision machining process. Selected features by which to partition the cluster of patterns were obtained by time series AR modeling of dynamic cutting force signals. The wear on a diamond tool edge appears to be classifiable into two types, micro-chipping and gradual, both very small compared to conventional tool wear. In this regard, we used a fuzzy technique in pattern recognition, which considers the ambiguity in classification as well as the weakness of the cutting force variation, to monitor the diamond tool wear status, with satisfactory results.
Issue Section:Research Papers
Topics:Diamond turning, Pattern recognition, Wear, Diamond tools, Cutting, Ambiguity, Crystals, Machining, Modeling, Signals, Time series
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Copyright © 1994
by The American Society of Mechanical Engineers