Performance investigation of fitting algorithms in surface micro-topography grinding processes based on multi-dimensional fuzzy relation set

Abstract

For the purpose of improving the resultant performance processes of microsurface precise grinding in different machining conditions, the obtained grinded surface should be quality-evaluated and influence-assessed under the instructions of topography modeling. Since microsurface fitting algorithms exerts a considerable influence on those constructed topography mathematical features in geometric domain, which results to different grinding micro-topography processes caused by one specific influence mechanism, and makes the performance investigation of fitting algorithms in surface micro-topography grinding processes indispensable. Through extracting the coordinate positions of those selected physical control points in one objective surface topography sample to be grinded by using a series of precise spatial coordinate measurement apparatuses, several typical algorithms of surface fitting in geometric domain were used for constructing the micro-topography models of those sample section surface with complicated point cloud. On the base of computing the newly proposed mathematical features caused from those micro-topography models, fuzzy evaluation data sequences were established and one new multi-dimensional mathematical quantitative evaluation method derived from fuzzy relation set was proposed and employed to deal with their inherent mutual-relationships. As the performance comparisons of resultant grinded topography between using surface modeling operations and not using surface modeling operations were clearly quantified, it is obvious that the multi-dimensional fuzzy influence relation set between surface fitting algorithms, topography geometric features, and practical grinding processes in different experimental conditions will be quantitatively analyzed in detail, which contributes to the acquirement of final conclusions concerned with the inherent influence mechanism and mutual mathematical relation set emerged from the performance results of different surface fitting algorithms, together with the topography spatial features and practical surface grinding process characteristics in one specific experimental conditions as well. Through realizing grinding processes evaluation based on multi-dimensional fuzzy relation set and making performance comparisons with several other typical statistical evaluation methods in index analysis, an in-depth performance inspection of surface precise grinding with objective micro-topography will be facilitated and optimized; simultaneously, a new research idea for improving microsurface modeling and its subsequent grinding processes in a practical experimental operation can also be demonstrated in the long run.