The Wavelet Transform for Feature Extraction and Surface Roughness Evaluation after Micromachining

Abstract

Miniaturization is a dominant trend in machine building which requires the use of advanced techniques of manufacturing and control. Apart from dimensional and shape precision of miniaturized components, surface geometry, particularly roughness and so-called microroughness that results from the use of advanced treatment techniques, plays an important role in correct assembly, reliable operation and durability of the whole machine. The selection of filtration method in surface geometry of micro-objects can be a substantial problem. The authors of the paper propose to use wavelet filtration in digital processing of a point cloud to remove measurement noise and not to change the surface character of the measured object. Also, the authors propose, in this paper, some criteria for selecting the number of wavelet filtration levels based on minimalization of the RMS value. It is supposed to improve the efficiency of low-pass filtration of small areas of the surface, particularly compared to traditional λs Gaussian filtration.