Temporal and frequential analysis of the tools wear evolution

The machining process monitoring plays a very significant role in the prevention of non-desired phenomena, such as excessive wear and the tool rupture. In this article, we use effective techniques based on the analysis of cutting force and vibratory signals measured for various cutting conditions. The proposed methodology uses some signal processing techniques, such as temporal, frequential approaches and the wavelet analysis. The objective of this work is to show, on one hand, the sensitivity of the scalar indicators to the flank wear variation, and on the other hand the determination of the influence of flank wear on the signals produced during a machining process. In this context the wear evolution results allow determining the abrupt changes that can detect the cutting tool damage.