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

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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.