• DocumentCode
    527503
  • Title

    Condition prediction of flue gas turbine based on Echo State Network

  • Author

    Xu, Xiao-li ; Chen, Tao ; Wang, Shao-hong

  • Author_Institution
    Sch. of Mech. & Vehicular Eng., Beijing Inst. of Technol., Beijing, China
  • Volume
    2
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    1089
  • Lastpage
    1092
  • Abstract
    Echo State Network is one pioneering recurrent neural network with the core structure of a randomly generated and unchangeable reservoir. This paper provides a Condition prediction model of flue gas turbine by applying Echo State Network and makes prediction of the overall vibration value. Compared to Elman neural network prediction model, examples show that Echo State Network has wonderful dynamic characteristics with smaller error and less prediction time. The model has a good performance in non-linear time series prediction, indicating that the model is feasible in the condition prediction of flue gas turbine.
  • Keywords
    condition monitoring; flue gases; gas turbines; power engineering computing; recurrent neural nets; time series; condition prediction; echo state network; flue gas turbine; nonlinear time series prediction; recurrent neural network; Artificial neural networks; Predictive models; Recurrent neural networks; Reservoirs; Training; Turbines; Vibrations; Condition Prediction; Echo State Network; Elman neural network; Flue Gas Turbine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5583012
  • Filename
    5583012