State Monitoring for Centrifugal Pump of PWR Based on HMM and SVM

Abstract:

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The centrifugal pump of pressurized water reactor (PWR) in nuclear power plant is characterized by its complicated system, small accumulated data and fault samples. HMM has a strong ability to deal with time series modeling for dynamic process, while SVM has excellent generalization ability to solve the learning problems with small samples. This paper develops a state monitoring system based on the hybrid HMM/SVM model. The wavelet analysis techniques are used to extract features and the Hidden Markov Model (HMM) and Support Vector Machine (SVM) are used as the basic modeling and identification tools. The identification results of centrifugal pump show that the hybrid HMM/SVM system is effective and available for the state monitoring of the centrifugal pump of PWR in nuclear power plan.

Info:

Periodical:

Advanced Materials Research (Volumes 97-101)

Edited by:

Zhengyi Jiang and Chunliang Zhang

Pages:

3233-3238

DOI:

10.4028/www.scientific.net/AMR.97-101.3233

Citation:

C. L. Zhang et al., "State Monitoring for Centrifugal Pump of PWR Based on HMM and SVM", Advanced Materials Research, Vols. 97-101, pp. 3233-3238, 2010

Online since:

March 2010

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Price:

$35.00

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