Bi-fractal feature of bi-Gaussian stratified surfaces

Abstract

Abstract Surface serves as the fingerprint of a component. Researchers have observed the bi-fractal feature of a surface roughness. The increasing number of researchers attempting to model the roughness from a bi-Gaussian stratified perspective provides the possibility of understanding the bi-fractal mechanism. Engineering (two-process and worn surfaces) and simulated surfaces are selected to establish a database of bi-Gaussian stratified surfaces. The bi-fractal feature of these bi-Gaussian stratified surfaces is analyzed, finding that the upper Gaussian component of a bi-Gaussian stratified feature reduces the power spectral density (PSD) and partially diverges the slope of the logarithmic PSD to render a bi-fractal behavior. The proportion of the components plays a greater role than the ratio of the component root-mean-square values.