The characteristics of the acoustic emission signal during the tool wear process in end milling are analyzed, and a signal processing scheme for abstracting the mean time domain averaging deviation of the signal to monitor tool wear is proposed. Experiments indicate that the mean deviation value is sensitive to flank wear and its normalized value is not as dependent on milling parameters as the acoustic emission root mean square signal.

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