A novel real-time fault diagnostic system by using strata hierarchical artificial neural network

doi:10.1109/APPEEC.2009.4918103

CORC > 兰州理工大学 > 兰州理工大学 > 机电工程学院

	A novel real-time fault diagnostic system by using strata hierarchical artificial neural network
	Yan, Changfeng 1,2; Zhang, Hao 2; Wu, Lixiao 1
	2009
会议日期	March 27, 2009 - March 31, 2009
会议地点	Wuhan, China
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
页码	1375-+
英文摘要	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.
会议录	Asia-Pacific Power and Energy Engineering Conference, APPEEC
会议录出版者	IEEE Computer Society
会议录出版地	345 E 47TH ST, NEW YORK, NY 10017 USA
语种	英语
ISSN号	21574839
WOS研究方向	Energy & Fuels
WOS记录号	WOS:000270497300323
内容类型	会议论文
源URL	[http://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
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]. 见:. Wuhan, China. March 27, 2009 - March 31, 2009.