RECURRENCE QUANTIFICATION ANALYSIS OF SYSTEM SIGNALS FOR DETECTING TOOL WEAR IN A LATHE

Abstract

ABSTRACT The work investigates applicability of recurrence quantification analysis (RQA) in metal cutting with an objective to detect tool wear. The effectiveness of applying a system input signal; the drive motor current, in relation to a system output signal; the tool vibration, for the analysis is also explored. The work establishes conclusively that three of the RQA variables, percent determinism, percent recurrence and entropy are sensitive to tool wear

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