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Fuzzy fault diagnosis system of MCFC
作者姓名:WangZhenlei  QianFeng  CaoGuangyi
作者单位:[1]InstituteofAutomatic,EastChinaUniversityofScienceandTechnology,Shanghai200237,P.R.China [2]InstituteofFuelCell,ShanghaiJiaotongUniversity,Shanghai200030,P.R.China
基金项目:theHighTechnologyResearchandDevelopmentProgrammeofChina (No.2 0 0 2AA5 170 2 0 )
摘    要:A kind of fault diagnosis system of molten carbonate fuel cell (MCFC) stack is proposed in this paper. It is composed of a fuzzy neural network (FNN) and a fault diagnosis element. FNN is able to deal with the information of the expert knowledge and the experiment data efficiently. It also has the ability to approximate any smooth system. FNN is used to identify the fault diagnosis model of MCFC stack. The fuzzy fault decision element can diagnose the state of the MCFC generating system, normal or fault, and can decide the type of the fault based on the outputs of FNN model and the MCFC system. Some simulation experiment results are demonstrated in this paper.

关 键 词:模糊故障诊断系统  碳酸盐燃料电池  模糊神经网络系统  电化学系统  自动化技术

Fuzzy fault diagnosis system of MCFC
WangZhenlei QianFeng CaoGuangyi.Fuzzy fault diagnosis system of MCFC[J].High Technology Letters,2005,11(1):72-74.
Authors:Wang Zhenlei  Qian Feng  Cao Guangyi
Abstract:A kind of fault diagnosis system of molten carbonate fuel cell (MCFC) stack is proposed in this paper. It is composed of a fuzzy neural network (FNN) and a fault diagnosis element. FNN is able to deal with the information of the expert knowledge and the experiment data efficiently. It also has the ability to approximate any smooth system. FNN is used to identify the fault diagnosis model of MCFC stack. The fuzzy fault decision element can diagnose the state of the MCFC generating system, normal or fault, and can decide the type of the fault based on the outputs of FNN model and the MCFC system. Some simulation experiment results are demonstrated in this paper.
Keywords:fault diagnosis  molten carbonate fuel cell  fuzzy neural network  fault decision element
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