Characterization of Machined Surface Topography Based on the Normal Declination Angle of Microfacets

Abstract

It is important to characterize surface topography in order to study machined surface characteristics. Due to the features of periodicity and randomness of machined surface topography, the existing topographical parameters may not describe its features accurately. A novel characterization method called the normal declination angle of microfacet-based surface topography is thus proposed for this task. The topography of machined surfaces is measured and the data on the normal declination angle are obtained. Then, surface topography is analyzed via the distribution of the normal declination angle. The lognormal distribution characterization model of machined surface topography is established, and the accuracy of the model is verified by error analysis. The results show that the calculated results of the present characterization model are generally consistent with the distribution of the normal declination angle, where the maximal root mean square errors (RMSE) is 4.5%. Therefore, this study may serve as an effective and novel way to describe the characteristics of the machined surface topography.

Illumination modelling for reconstructing the machined surface topography

“…Hence, the normal declination angle can reflect the geometric characteristics of the corresponding surface topography. Our previous research results show that the machined surface topography has the geometric features of lognormal distribution [20], which can be expressed as…”