Abstract
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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Bae, H., Chun, SP., Kim, S. (2006). Predictive Fault Detection and Diagnosis of Nuclear Power Plant Using the Two-Step Neural Network Models. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_62
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DOI: https://doi.org/10.1007/11760191_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34482-7
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