Experimental study of tool life transition and wear monitoring in turning operation using a hybrid method based on wavelet multi-resolution analysis and empirical mode decomposition

This paper deals with the experimental study of the tool life transition and the wear monitoring during the turning operation of AISI D3 steel workpiece using coated carbide tool inserts (TiCN/Al2O3/TiN). A hybrid method, based on the combination of wavelet multi-resolution analysis (WMRA) and Empirical Mode Decomposition (EMD), is proposed to analyze vibratory signals acquired during the machining process. Using the mean power and the energy as main scalar indicators, the proposed method has been optimized and evaluated in several configurations including the cutting speed, the feed rate, and the depth of cut. The results show that the proposed hybrid method (WMRA/EMD) gives better evaluation of the tool state and the wear monitoring compared to the application of WMRA or EMD alone.