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Martin Todd, Stephen D. J. McArthur, J. R. McDonald, and Sally J. Shaw, "A semiautomatic approach to deriving turbine generator diagnostic knowledge," IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews, Vol. 37, No. 5, pp. 979-992, 2007.

has been cited by the following article:

• TITLE: A Novel Real-Time Fault Diagnostic System for Steam Turbine Generator Set by Using Strata Hierarchical Artificial Neural Network

  AUTHORS: Changfeng YAN, Hao ZHANG, Lixiao WU

  KEYWORDS: real-time, fault diagnosis, strata hierarchical artificial neural network, fuzzy CMAC

  JOURNAL NAME: Energy and Power Engineering, Vol.1 No.1, August 18, 2009

  ABSTRACT: 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.