Acoustic signal analysis for prediction of flank wear during conventional milling

Travis Roney, Anthony Bauccio, Derek Shaffer, Paige Lorson, Ihab Ragai, David Loker, Chetan Nikhare

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationAdvanced Manufacturing
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791852019
DOIs
StatePublished - Jan 1 2018
EventASME 2018 International Mechanical Engineering Congress and Exposition, IMECE 2018 - Pittsburgh, United States
Duration: Nov 9 2018Nov 15 2018

Publication series

NameASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
Volume2

Other

OtherASME 2018 International Mechanical Engineering Congress and Exposition, IMECE 2018
CountryUnited States
CityPittsburgh
Period11/9/1811/15/18

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering

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  • Cite this

    Roney, T., Bauccio, A., Shaffer, D., Lorson, P., Ragai, I., Loker, D., & Nikhare, C. (2018). Acoustic signal analysis for prediction of flank wear during conventional milling. In Advanced Manufacturing (ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE); Vol. 2). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/IMECE2018-86886