Discrete properties of random surfaces

Abstract

The problem of measuring surface parameters of tribological importance such as peak curvature has been considerably simplified. Using discrete random process analysis tribological parameters of a wide range of surfaces can now be expressed and measured in terms of just two points on the measured autocorrelation function and the r.m.s. value of the surface. In addition, the contribution each ' scale of size ’ of asperity makes to an overall parameter can be assessed quantitatively. Many new expressions relating tribological parameters to the autocorrelation function have been derived using a limiting procedure which produces results entirely consistent with equivalent continuous theory. Using this theory it is now possible to predict ‘gap’ parameters between two surfaces in contact in terms of simple additive parameters of each surface. Finally a new statistical model of the surface has been developed which encompasses many types of engineering surface.