Processing acoustic emission signal data for characterising cutting tool wear and chip management

Abstract

The paper is concerned with monitoring tool wear using Acoustic Emission (A. E. ) sensors. The sensitivity of A. E. to chip form is substantiated. It is shown that strain rate is a predominant parameter governing A. E. activity in metal cutting. The semi-empirical cutting theory due to Oxley and Hastings successfully predicts trends in the A. E. r. m. s. signal for a variety of semi-orthogonal cutting conditions and offers potential for development of a computer based tool wear monitoring system