NDLI: Parameter Identification of Vibration Loads of Hydro Generator Using Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Lijuan Cao Shouju Li Zichang Shangguan
Copyright Year	2008
Description	Author affiliation: Inst. of Mech. Eng., Dalian Fisheries Univ., Dalian (Lijuan Cao)
Abstract	Vibrating dynamic characteristics have been a major unknown in the modeling and mechanical analysis of large hydro generators. An identification algorithm for vibrating dynamic characterization by using artificial neural network is developed for multi-degree-offreedom systems. By making use of measured dynamic responses of the hydro generator at Fengman Hydropower Plant, the estimation algorithm identifies the loading parameters which include the main frequencies and amplitudes of vibrating forces. The artificial neural network is used to tackle an illposed problem of the parameter identification. Artificial neural network abilities to approximate nonlinear functions and capture complex relationships in the data are instrumental abilities which could support the loading parameter identification. It is demonstrated that a well trained artificial neural network reveals an extremely fast convergence and a high degree of accuracy in the parameter identification of hydro generator vibration.
Starting Page	428
Ending Page	428
File Size	437969
Page Count	1
File Format	PDF
ISBN	9780769531618
DOI	10.1109/ICICIC.2008.415
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nickel Manganese
Content Type	Text
Resource Type	Article

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