학술논문

Wavelet Analysis for the Extraction of Morphological Features for Orthopaedic Bearing Surfaces
Document Type
TEXT
Source
Subject
Language
English
Abstract
Surface texture is one of the most critical factors and important functionality indicators inthe performance of high precision and nanoscale devices and components. The functionsthat 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 inoperational service is determined by roughness, waviness and the multi-scalar topographicfeatures of a surface, such as random peaks/pits and ridges/valleys. These functionaltopographical features will impact directly on wear mechanics and physical properties of awhole 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 highcontact stresses and abrasion; consequently wear particles and debris will be generated bysuch surface topographical features, whereas the pits and valleys will affect the lubricationand fluid retention properties. In this situation, a vitally important consideration forfunctional characterisation must be the appropriate separation of the different componentsof surfaces, which is not only to extract roughness, waviness and form error, but should alsobe extended to all multi-scalar topographical events over surfaces.