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

被引:0
|
作者
Xu, XiangBin [1 ]
机构
[1] E China Jiaotong Univ, Sch Mechatron Engn, Nanchang 330013, Peoples R China
关键词
HSFDONES; Ontology; Fault Diagnosis; Self-learning; Data Mining;
D O I
暂无
中图分类号
S [农业科学];
学科分类号
09 ;
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 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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页码:460 / 466
页数:7
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