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Acoustic Signal Analysis for Prediction of Flank Wear During Conventional Milling

[+] Author Affiliations
Travis Roney, Anthony Bauccio, Derek Shaffer, Paige Lorson, Ihab Ragai, David Loker, Chetan Nikhare

Penn State University - Behrend College, Erie, PA

Paper No. IMECE2018-86886, pp. V002T02A004; 5 pages
  • ASME 2018 International Mechanical Engineering Congress and Exposition
  • Volume 2: Advanced Manufacturing
  • Pittsburgh, Pennsylvania, USA, November 9–15, 2018
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5201-9
  • Copyright © 2018 by ASME


In recent years, the investigation of the acoustic signals (AS) produced from different machining processes have primarily focused on the ultrasonic frequency range. The objective of this work is to propose a novel technique for predicting the flank wear condition of a tool and ultimately tool failure (insert chipping) during the process of conventional face milling. Preliminary experiments suggest that the spectral content of audible acoustic emission (AAE) signals could be used to predict the cumulative flank wear in real time for an indexable carbide insert during the milling process. The experiments conducted for this study suggest a strong correlation between the magnitudes of the AAE in the selected frequency range, and the amount of wear on the insert.

Copyright © 2018 by ASME
Topics: Wear , Acoustics , Milling , Signals



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