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
Link To Document :
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