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http://dx.doi.org/10.9723/jksiis.2020.25.6.001

Development of Nuclear Power Plant Instrumentation Signal Faults Identification Algorithm  

Kim, SeungGeun (한국원자력연구원 미래전략본부 지능형컴퓨팅연구실)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.25, no.6, 2020 , pp. 1-13 More about this Journal
Abstract
In this paper, the author proposed a nuclear power plant (NPP) instrumentation signal faults identification algorithm. A variational autoencoder (VAE)-based model is trained by using only normal dataset as same as existing anomaly detection method, and trained model predicts which signal within the entire signal set is anomalous. Classification of anomalous signals is performed based on the reconstruction error for each kind of signal and partial derivatives of reconstruction error with respect to the specific part of an input. Simulation was conducted to acquire the data for the experiments. Through the experiments, it was identified that the proposed signal fault identification method can specify the anomalous signals within acceptable range of error.
Keywords
Nuclear power plant; Instrumentation signals; Signal fault identification; Variational autoencoder; Design basis accident;
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Times Cited By KSCI : 4  (Citation Analysis)
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