Micro-end-milling---III. wear estimation and tool breakage detection using acoustic emission signals

摘要

Acoustic Emission (AE) signals have been used to monitor tool condition in conventional machiningoperations. In this paper, new procedures are proposed to detect tool breakage and to estimate toolcondition (wear) by using AE. The proposed procedure filters the AE signals with a narrow band-width, band-pass filter and obtains the upper envelope of the harmonic signal by using analoghardware. The envelope is digitized, encoded and classified to monitor the machining operation. Thecharacteristics of the envelope of the AE were evaluated to detect tool breakage. The encodedparameters of the envelope of the AE signals were classified by using the Adaptive Resonance Theory(ART2) and Abductory Induction Mechanism (AIM) to estimate wear. The proposed tool breakageand wear estimation techniques were tested on the experimental data. Both methods were found tobe acceptable. However, the reliability of the tool breakage detection system was higher than thewear estimation method.