Abstract
A method for characterizing the surface topography at several length scales is presented. The analysis is based on a log–log representation of a characteristic roughness parameter versus the length scale. It is applicable to fractal and non-fractal surfaces. The potential of the method is evaluated by applying it to the characterization of computed self-affine fractal profiles of different fractal dimension. Profiles of titanium surfaces with different morphologies were measured with an optical profilometer and with an atomic force microscope. Variable length scale analysis of the data was performed for the roughness parameters root mean square deviation, skewness and kurtosis. Results show that the proposed method of data evaluation yields detailed information on length scale dependent surface topography, not available with classical roughness determinations.
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