Wavelet and fractal approach to surface roughness characterization after finish turning of different workpiece materials

In this paper, the surface profiles generated in longitudinal turning operations were characterized using continuous wavelet transform (CWT) and normalized fractal dimension Dn. In the comparative analysis, some characteristic roughness profiles after the turning of different workpiece materials, such as C45 medium carbon steel, nodular cast iron and hardened (55 HRC) high-strength alloy steel were selected. For wavelet characterization, both Morlet and ‘Mexican hat’ analyzing wavelets, which allow the assessment of extrema and frequency distribution, were utilized. The results of the CWT as a function of profile and momentary wavelet length are presented. It is concluded that CWT can be useful for the analysis of the roughness profiles generated by cutting processes. Moreover, the wavelet transform together with fractal dimension can be capable of the detection of local self-similarity in the surface profile.