Classification of tribological surfaces

The reliable and accurate 3-D characterization and classification of tribological surfaces is still a challenging problem. Many tribological surfaces exhibit topographical features over a wide range of scales; ranging from nano-scales (atomic or molecular scales) to micro-scales (up to hundred micrometer scales). There are several surface topography characterization methods that exist today. However, due to the non-stationary and multi-scale nature of tribological surfaces even for the moderately complicated topography of a tribological surface, these methods provide a limited description. Recently a new method, based on fractal modelling, has been developed and applied to the characterization of tribological surfaces. The method involves construction of a mathematical model, called a partition iterated function system (PIFS), for surface data. This model encapsulates complete information about the surface 3-D data. Iterative application of this model into any initial image results in a sequence of images converging to the original surface image. Based on this method a pattern recognition system has been developed and applied to the classification of tribological surfaces. Recently, the work has been conducted on the improvement of the PIFS method. An attempt was made to apply both fractals and wavelets to analyze surface topography data. It was thought that since the fractal method allows the characterization of surface topography over the widest achievable range of scales and the wavelet method provides the characterization of surface topography at individual scales a combination of these two methods could provide the most accurate results. The hybrid fractal-wavelet method has recently been developed and applied to the characterization of tribological surfaces. In this paper it is demonstrated that it is possible to both characterize and classify tribological surfaces without the need for any surface parameters, with unique precision and accuracy. Also a short overview of recent advances and developments in the characterization and classification of tribological surfaces is presented.