Tool Wear Estimation from Acoustic Emissions: A Model Incorporating Wear-Rate

(CAAR) is a consortium of researchers from six universities working in partnership with Department of Defense laboratories and industry. CAAR is funded by the Office of Naval Research through a 1997 Department of Research Initiative. Abstract Almost all prior work on modelling the dependance of acoustic emissions on tool wear have concentrated on the effect of wear-level on the sound. We give justification for including the wear-rate information contained in the sound to improve estimation of wear. A physically plausible model is proposed which results in a Hidden Markov Model (HMM) whose hidden states are the wear level and rate and observations are the feature vectors extracted from the sound. We also present an efficient method for picking feature vectors that are most useful for the classification problem.