A Web-Based Remote Intelligent Expert System for Ferrography Diagnosis

Abstract

A ferrography expert system for wear particle analysis can be an effective means of condition monitoring and fault diagnosis. The knowledge of the ferrography diagnosis expert system cannot be represented by certain rules because it is fuzzy and random, therefore an intelligent expert system is developed. A neural network with self-deleting nodes is employed in the intelligent expert system, and this overcomes to some degree the disadvantages of a traditional expert system and makes it possible to automatically acquire knowledge by learning from samples and to realize entirely automatic processing, from wear particle recognition to wear diagnosis.