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http://dx.doi.org/10.5391/JKIIS.2005.15.6.673

Fault Diagnosis for the Nuclear PWR Steam Generator Using Neural Network  

Lee, In-Soo (School of Electronic and Electrical Engineering, Sangju National University)
Yoo, Chul-Jong (School of Electronic and Electrical Engineering, Sangju National University)
Kim, Kyung-Youn (Department of Electronic Engineering, Cheju National University)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.15, no.6, 2005 , pp. 673-681 More about this Journal
Abstract
As it is the most important to make sure security and reliability for nuclear Power Plant, it's considered the most crucial issues to develop a fault detective and diagnostic system in spite of multiple hardware redundancy in itself. To develop an algorithm for a fault diagnosis in the nuclear PWR steam generator, this paper proposes a method based on ART2(adaptive resonance theory 2) neural network that senses and classifies troubles occurred in the system. The fault diagnosis system consists of fault detective part to sense occurred troubles, parameter estimation part to identify changed system parameters and fault classification part to understand types of troubles occurred. The fault classification part Is composed of a fault classifier that uses ART2 neural network. The Performance of the proposed fault diagnosis a18orithm was corroborated by applying in the steam generator.
Keywords
Fault detection; fault isolation; parameter estimation; ART2 NN; nuclear PWR steam generator;
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