HSFDONES: A Self-Leaning Ontology-Based Fault Diagnosis Expert System Framework - Archive ouverte HAL Access content directly
Conference Papers Year : 2011

HSFDONES: A Self-Leaning Ontology-Based Fault Diagnosis Expert System Framework

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Xiangbin Xu
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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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Dates and versions

hal-01564878 , version 1 (19-07-2017)

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Attribution - CC BY 4.0

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Xiangbin Xu. HSFDONES: A Self-Leaning Ontology-Based Fault Diagnosis Expert System Framework. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. pp.460-466, ⟨10.1007/978-3-642-18369-0_54⟩. ⟨hal-01564878⟩
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