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Z. S. Chen, Y. M. Yang, Z. Hu, and G. J. Shen, "Detecting and predicting early faults of complex rotating machinery based on cyclostationary time series model," Journal of Vibration and Acoustics, Transactions of the ASME, Vol. 128, pp. 666-671, 2006.

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.