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

摘要：

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 diag-nosis data warehouse is built, the decision tree and Apriori algorithm are used to acquire fault knowledge to realize HSFDONESs ontology selflearning. HSFDONES offers system framework for building intelligent fault diagnosis system. Finally the agricultural machinerys hydraulic fault diagnosis expert system was developed on the basis of the framework.

关键词： HSFDONES Ontology Fault Diagnosis Self-learning Data Mining.

作者: XiangBin Xu

作者单位: School of Mechatronics Engineering, East China Jiaotong University,330013 Nanchang, P.R. China

会议类型: 国际会议

会议名称: The 4th IFIP International on Computer and Computing Technologies in Agriculture and the 4th Symposium on Development of Rural Information(第四届国际计算机及计算机技术在农业中的应用研讨会暨第四届中国农业信息化发展论坛 CCTA 2010)

会议地点: 南昌

会议语种:英文

页码: 460-466

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）