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Nuclear science and engineering, 1994-04, Vol.116 (4), p.313-325
1994
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Details

Autor(en) / Beteiligte
Titel
Detecting Faults in a Nuclear Power Plant by Using Dynamic Node Architecture Artificial Neural Networks
Ist Teil von
  • Nuclear science and engineering, 1994-04, Vol.116 (4), p.313-325
Ort / Verlag
La Grange Park, IL: Taylor & Francis
Erscheinungsjahr
1994
Beschreibungen/Notizen
  • An artificial neural network (ANN)-based diagnostic adviser capable of identifying the operating status of a nuclear power plant is described. A dynamic node architecture scheme is used to optimize the architectures of the two backpropagation ANNs that embody the adviser. The first or root network is used to determine whether or not the plant is in a normal operating condition. If the plant is not in a normal condition, the second or classifier network is used to recognize the particular off-normal condition or transient taking place. These networks are developed using simulated plant behavior during both normal and abnormal conditions. The adviser is effective at diagnosing 27 distinct transients based on 43 scenarios simulated at various severities that contain up to 3% noise.

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