Basic computational tools and mechanical hardware for torque-based diagnostic of machining operations

Abstract

In the industry, only rotary dynamometers can be used for monitoring when multiple spindles are used in machining operations. The current commercial rotary dynamometers are bulky and expensive for most machining centers. The basic hardware and computational tools proposed are for a smaller, more cost effective Torque-based Machining Monitor (TbMM). The objective of the TbMM concept is to estimate the remaining tool life, detect chatter from the torque signal inside the proposed device, and communicate with the central computer only when problems arise. The remaining tool life estimation and chatter detection algorithms of the TbMM were developed by analyzing the experimental data collected by a commercial rotary dynamometer. The mechanical hardware of the TbMM was designed to generate voltage proportional to the cutting torque using a piezoelectric composite element. The remaining tool life was estimated from the standard deviation (or variance) of the torque signal. Teager-Kaiser algorithm (TKA) based procedure detected the chatter based on the frequency estimations only from four samples at a time. The accuracy and characteristics of the signal of the mechanical component of the TbMM were found satisfactory in the estimation of machining problems such as wear and chatter. The TbMM is a good choice particularly when multiple spindles work simultaneously on the same workpiece.