Predictive Fault Detection and Diagnosis of Nuclear Power Plant Using the Two-Step Neural Network Models

  • Hyeon Bae
  • Seung-Pyo Chun
  • Sungshin Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)


Operating the nuclear power generations safely is not easy way because nuclear power generations are very complicated systems. In the main control room of the nuclear power generations, about 4000 numbers of alarms and monitoring devices are equipped to handle the signals corresponding to operating equipments. Thus, operators have to deal with massive information and to analyze the situation immediately. In this paper, the fault diagnosis system is designed using 2-steps neural networks. This diagnosis method is based on the pattern of the principal variables which could represent the type and severity of faults.


Nuclear Power Plant Neural Network Model Steam Generator Failure Detection Failure Type 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hyeon Bae
    • 1
  • Seung-Pyo Chun
    • 1
  • Sungshin Kim
    • 1
  1. 1.School of Electrical and Computer EngineeringPusan National UniversityBusanKorea

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