Use of cutting force and vibro-acoustic signals in tool wear monitoring based on multiple regression technique for compreg milling

Abstract

This study focused on a computerised TCM (tool condition monitoring) system as a part of automated monitoring of the machining processes in the wood industry. The system’s principal task was to evaluate the actual state of tool wear without disrupting the normal course of machine tool exploitation for cutting force and vibro-acoustic signals analysis. During the experiment, five physical quantities that are generated during machining were measured and recorded: cutting forces in two directions (Fx, Fy), ultrasonic stress waves (acoustic emission – AE), acoustic pressure in the range of audible frequencies (noise – N), and acceleration of mechanical vibrations (V). Six pairs of tools were used in the experiment. One tool from each pair was experimental, the other was a control tool. Out of the five physical quantities generated during machining that were tested as an indirect source of information on the tool condition, signals of cutting forces and mechanical vibrations proved the most useful. Both acoustic emission and noise signals emerged as wholly inadequate as evidence to predict tool wear.