MONITORING END-MILL WEAR AND PREDICTING TOOL FAILURE USING ACCELEROMETERS

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

8 Scopus citations

Abstract

Autoregressive models are fit to end-milling acceleration data and the Data Dependent Systems methodology is utilized to isolate the modal energies of the first and second multiples of the tooth pass frequency. The modal energies are shown to be closely linked to the wear curve and a detection scheme is developed that is capable of tracking the end-mill’s wear and providing an early warning of impending failure. Six life tests are conducted under varying conditions to demonstrate the capabilities of the detection scheme: standard cutting conditions, extreme cutting conditions, premature catastrophic failure and accelerometer placement. In all six cases, the detection scheme was able to provide a warning of impending failure several centimeters before the failure occurred.

Original languageEnglish (US)
Title of host publicationManufacturing Science and Engineering
PublisherAmerican Society of Mechanical Engineers (ASME)
Pages867-875
Number of pages9
ISBN (Electronic)9780791816066
DOIs
StatePublished - 1998
EventASME 1998 International Mechanical Engineering Congress and Exposition, IMECE 1998 - Anaheim, United States
Duration: Nov 15 1998Nov 20 1998

Publication series

NameASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
Volume1998-R

Conference

ConferenceASME 1998 International Mechanical Engineering Congress and Exposition, IMECE 1998
Country/TerritoryUnited States
CityAnaheim
Period11/15/9811/20/98

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering

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