1. Improvement of fault diagnosis efficiency in nuclear power plants using hybrid intelligence approach.
- Author
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Liu, Yong-kuo, Xie, Chun-li, Peng, Min-jun, and Ling, Shuang-han
- Subjects
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NUCLEAR power plants , *ELECTRIC power system faults , *SCIENTIFIC observation , *ARTIFICIAL neural networks , *DATA fusion (Statistics) , *GRAPH theory - Abstract
Different types of faults could occur in a nuclear power plant, and there was no direct correspondence between a specific fault and its symptoms. So, a hybrid intelligence approach is proposed for the fault diagnosis at a nuclear power plant. Depending up the symptoms observed and the progress of fault diagnosis process, different fault diagnosis technologies, such as artificial neural network, data fusion and signed directed graph, could be combined as appropriate to detect and identify different faults at local or global level in nuclear power plants. The effectiveness of hybrid intelligence approach in improving the fault diagnosis efficiency in nuclear power plants was verified through simulation experiments. [ABSTRACT FROM AUTHOR]
- Published
- 2014
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