Surface topography separation based on wavelet reconstruction and empirical mode decomposition

Surface topography decomposition used to identify the components of the machined surface is an important method for tracing machining errors and predicting surface performance. This paper presents a generalized and practical method to fulfill the surface topography decomposition by wavelet reconstruction and Empirical Mode Decomposition (EMD). Firstly, by choosing suitable base function, wavelet transformation technique was applied for surface decomposition to get surface components in different level, with some levels containing uncertain information, indicating that wavelet transform was not an ideal method to get genuine components of machined surface. EMD was applied for further decomposition, EMD can obtain genuine components of surface, mode mixing occurred when surface contained noise and impulse. A hybrid method combining the merits of wavelet and EMD was proposed to eliminate noise and impulse in surface, then genuine components of surface was obtained. Finally, the proposed method was applied to a measured 1-D surface, and its genuine components were gotten respectively. Further Fourier Transform was used to confirm the result which indicates that proposed method can correctly get genuine components of the machined surface. The method proposed in this article will give a practical guidance for surface components analysis and provide a base for further study such as tracing processing and predicting performance of surface according its components.