A novel real-time fault diagnostic system by using strata hierarchical artificial neural network | |
Yan, Changfeng1,2![]() ![]() | |
2009 | |
会议名称 | 2009 Asia-Pacific Power and Energy Engineering Conference, APPEEC 2009 |
会议录名称 | Asia-Pacific Power and Energy Engineering Conference, APPEEC
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页码 | 1375-+ |
会议日期 | March 27, 2009 - March 31, 2009 |
会议地点 | Wuhan, China |
出版地 | 345 E 47TH ST, NEW YORK, NY 10017 USA |
出版者 | IEEE Computer Society |
摘要 | The real-time fault diagnosis system is very great important for steam turbine generator set due to a serious fault results in a reduced amount of electricity supply in power plant. A novel real-time fault diagnosis system is proposed by using strata hierarchical fuzzy CMAC neural network. A framework of the fault diagnosis system is described. Hierarchical fault diagnostic structure is discussed in detail. The model of a novel fault diagnosis system by using fuzzy CMAC are built and analyzed. A case of the diagnosis is simulated. The results show that the real-time fault diagnostic system is of high accuracy, quick convergence, and high noise rejection. It is also found that this model is feasible in real-time fault diagnosis. This electronic document is a "live" template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document. © 2009 IEEE. |
关键词 | Failure analysis Fault tolerant computer systems Fuzzy inference Fuzzy neural networks Steam power plants Steam turbines Turbogenerators Electronic document Fault diagnosis systems FUZZY-CMAC Hierarchical Artificial Neural Networks Hierarchical neural networks Real-time fault diagnosis Real-time fault diagnostics Steam turbine-generator set |
DOI | 10.1109/APPEEC.2009.4918103 |
收录类别 | EI |
语种 | 英语 |
WOS研究方向 | Energy & Fuels |
WOS类目 | Energy & Fuels |
WOS记录号 | WOS:000270497300323 |
EI入藏号 | 20093512276165 |
EI主题词 | Fault detection |
ISSN | 21574839 |
来源库 | Compendex |
分类代码 | 614 Steam Power Plants - 617.2 Steam Turbines - 705.2 Electric Generators - 722.4 Digital Computers and Systems - 723.4 Artificial Intelligence - 723.4.1 Expert Systems |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | https://ir.lut.edu.cn/handle/2XXMBERH/117075 |
专题 | 机电工程学院 |
通讯作者 | Yan, Changfeng |
作者单位 | 1.Lanzhou Univ Technol, Sch Mech & Elect Engn, Lanzhou, Peoples R China 2.Tongji Univ, CIMS Res Ctr, Shanghai, Peoples R China |
第一作者单位 | 兰州理工大学 |
通讯作者单位 | 兰州理工大学 |
推荐引用方式 GB/T 7714 | Yan, Changfeng,Zhang, Hao,Wu, Lixiao. A novel real-time fault diagnostic system by using strata hierarchical artificial neural network[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE Computer Society,2009:1375-+. |
条目包含的文件 | 条目无相关文件。 |
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