Chapter 3 Wavelet Analysis for the Extraction of Morphological Features for Orthopaedic Bearing Surfaces

Abstract

Surface texture is one of the most critical factors and important functionality indicators in the performance of high precision and nanoscale devices and components. The functions

that have been identified in various studies include wear, friction, lubrication, corrosion,

fatigue, coating, paintability, etc. [1-3]. It is also reported that the wear rates of surfaces in

operational service is determined by roughness, waviness and the multi-scalar topographic

features of a surface, such as random peaks/pits and ridges/valleys. These functional

topographical features will impact directly on wear mechanics and physical properties of a

whole system, such as hip joint replacement system in bioengineering [4-9]. For example,

during functional operation of interacting surfaces, peaks and ridges will act as sites of high

contact stresses and abrasion; consequently wear particles and debris will be generated by

such surface topographical features, whereas the pits and valleys will affect the lubrication

and fluid retention properties. In this situation, a vitally important consideration for

functional characterisation must be the appropriate separation of the different components

of surfaces, which is not only to extract roughness, waviness and form error, but should also

be extended to all multi-scalar topographical events over surfaces.