Analysis of signals for monitoring of nonlinear and non-stationary machining processes

An investigation of cutting process monitoring based on dynamic force and acceleration signals in the frequency and time-frequency domains is presented in this paper. The performance of a new data analysis technique, the Hilbert-Huang Transform (HHT), is used to analyze this process in frequency and time-frequency domain. This technique is also compared with the traditional Fourier transform method power spectra in the frequency domain approach. A comparison is made of the analysis of two commonly used signals: acceleration and dynamic force. The shift of the main frequency peak into lower frequencies and higher frequency fluctuations is considered as a cutter tool wear indicator. The appearance of new frequency indicates a cutter tool fault. The performance of dynamic cutting force signal using both HHT and Fourier transform shows better results within this study. The HHT (which deals with nonlinear and non-stationary signals) has been shown to be a robust tool for estimating cutter tool wear/fault.