Evaluation of critical wear transition loads of MMCs by rule based fuzzy modelling

Abstract

The evaluation of critical transition loads in a wear system of metal matrix composites (MMCs) was attempted with the aid of the wear knowledge established using fuzzy rule based modelling. The model presumes that the membership function of the inputs and the rule base are proper. The membership function of the output is adjusted to minimise the error between the predicted output and the experimental results. The influencing parameters considered in this paper include particle size, composite hardness and particle volume fraction, The method shows its unique advantage to model the wear of the complex system with metal matrix composites.

Applications of computational intelligence to mechanical engineering

“…Genetic Algorithms have been also employed [261]- [266], as well as some examples of fuzzy applications have been found in tribology [267]- [269] and in the specific field of lubrication [267], [270], [271].…”