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.
- Manufacturing Engineering Division
Recurrence Quantification Analysis of System Signals for Detecting Tool Wear in a Lathe
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Govindan, RV, & Narayanan, NNV. "Recurrence Quantification Analysis of System Signals for Detecting Tool Wear in a Lathe." Proceedings of the ASME 2015 International Manufacturing Science and Engineering Conference. Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing. Charlotte, North Carolina, USA. June 8–12, 2015. V002T04A005. ASME. https://doi.org/10.1115/MSEC2015-9214
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