Statistical Analysis Of Random And Pseudo Random Rough Surfaces (original) (raw)

Surface Measurement and Characterization, 1989

Abstract

For many years we have developed a method to reconstruct the profiles of statistically rough surfaces. This method is based on a microdensitometer analysis of electron micrographs of shadowed surface replicas. From the quantized profiles it is possible to compute the statistical moments -particularly the second order one called autocovariance function (ACF)- that characterize the surface. In general ACF's for pseudorandom surfaces are not decreasing monotonic functions and some complications arise when the definition of a auto-covariance length for those surfaces is considered. Solutions are proposed to overcome them; in particular, it seems preferable to deduce certain statistical parameters from the spectrum instead of the ACF. Moreover a new approach based on the minimal spanning tree (MST) -which is a graph constructed on the set of points representing the position of features on a surface- is proposed to study statistically order and disorder in the distribu-tion of these features.

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