HSFDONES: A self-leaning ontology-based fault diagnosis expert system framework

Abstract

HSFDONES is an expert system fault diagnosis which makes the fault diagnosis working more intelligently, HSFDONES uses the ontology-based self-leaning theory and technology to build fault diagnosis expert system. The fault diagnosis knowledge structure is defined and the relevant structure ontology and core fault ontology is researched in HSFDONES; the fault diagnosis data warehouse is built, the decision tree and Apriori algorithm are used to acquire fault knowledge to realize HSFDONES's ontology self-learning. HSFDONES offers system framework for building intelligent fault diagnosis system. Finally the agricultural machinery's hydraulic fault diagnosis expert system was developed on the basis of the framework. © 2011 IFIP International Federation for Information Processing.