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.
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Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-347 (Part IV), pp.460-466, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18369-0_54〉
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Xiangbin Xu. HSFDONES: A Self-Leaning Ontology-Based Fault Diagnosis Expert System Framework. Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-347 (Part IV), pp.460-466, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18369-0_54〉. 〈hal-01564878〉

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