The Detection of Short Time-Scale Tool Degradation Events during Face Milling Operations Using Cutting Force and Acoustic Emission

Abstract
Experimental data are presented on the effects of short time-scale events on measured cutting force and acoustic emission during face milling. The events of interest are those that occur within a few revolutions of the cutting tool and are associated with non-continuous degradation such as insert edge chipping. A processing scheme is suggested whereby the events are recognized and distinguished from each other using a neural network simulation applied to the peaks of the r.m.s. acoustic emission records. It is found that acoustic emission is a more suitable description of such events than is cutting force. Finally, a record of the network simulation acting as a breakage detector in real time on a computer numerical control (CNC) milling machine is presented.