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