Prediction of the catastrophic tool failure in hard turning through acoustic emission

Abstract

The paper deals with a new concept for the detection and prediction of the catastrophic tool failure (CTF) of ceramic inserts using an acoustic emission (AE) technique and an associated analysis of the chip formation during hard turning of bearing steel 100Cr6. The suggested method is based on the application of two sensors and the ratios of parameters of the acoustic emission such as AE RMS, AE absolute energy, and AE strength. The specific character of the segmented chips during hard turning is associated with the raw acoustic signals as well as the extracted AE features. The paper indicates that the conventional data processing of acoustic emission signals enables the detection of CTF. Tool wear connected with the cutting edge micro-chipping is related to the slow increase of tool wear (mainly flank wear VB) and stable values of AE features in the normal phase of tool wear. The CTF alters the AE waveforms as well as the course of the AE features. Conventional AE signal processing enables the detection of tool breakage. However, approaching CTF itself cannot be reliably predicted. Hence, a new concept of AE processing based on the ratios of the extracted AE features obtained in the different frequency ranges is suggested.