Tool wear detection in milling—An original approach with a non-dedicated sensor

Abstract

The aim of increasing productivity often makes optimising processes a priority and a means of anticipating defects. Metal cutting conditions are monitored to detect tool wear or breaks, so as to protect both machines and workpieces. Such monitoring relies on many different signals though two main approaches can be considered. The first consists in adding numerous sensors to the machine to obtain specific information, such as vibrations and cutting forces. The second consists in using information, often current or shaft power consumption, that can already be obtained from the machine and detected by standard sensors. This work focuses on the second approach that relies on using the sensors already installed, but optimising their capacities to the maximum for use under industrial conditions. The spindle rotary encoder signal is acquired through two systems: the first uses classical time-sampling while the second uses specific angular-sampling methodology. The differences between the two rotational frequency calculation technologies are described and discussed before focusing on the second methodology. Comparisons of cutting forces and variations in spindle rotational frequency reveal considerable similarities. Thus the occurrence of tool wear can be observed by monitoring variations in rotational frequency, and the genesis of tool tooth breaks can be established. Finally, we establish criteria for critical wear detection in both time and frequency domains.