Error prediction for a nuclear power plant fault-diagnostic advisor using neural networks
Journal Article
·
· Nuclear Technology; (United States)
OSTI ID:7006588
- Iowa State Univ., Ames, IA (United States). Dept. of Mechanical Engineering
The objective of this research is to develop a fault-diagnostic advisor for nuclear power plant transients that is based on artificial neural networks. A method is described that provides an error bound and therefore a figure of merit for the diagnosis provided by this advisor. The data used in the development of the advisor contain ten simulated anomalies for the San Onofre Nuclear Power Generating Station. The stacked generalization approach is used with two different partitioning schemes. The results of these partitioning schemes are compared. It is shown that the advisor is capable of recognizing all ten anomalies while providing estimated error bounds on each of its diagnoses.
- OSTI ID:
- 7006588
- Journal Information:
- Nuclear Technology; (United States), Journal Name: Nuclear Technology; (United States) Vol. 108:2; ISSN 0029-5450; ISSN NUTYBB
- Country of Publication:
- United States
- Language:
- English
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ANIMALS
DIAGNOSTIC TECHNIQUES
ENRICHED URANIUM REACTORS
MAMMALS
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NUCLEAR FACILITIES
NUCLEAR POWER PLANTS
PERSONNEL
POWER PLANTS
POWER REACTORS
PRIMATES
PWR TYPE REACTORS
REACTOR MONITORING SYSTEMS
REACTOR OPERATORS
REACTOR SAFETY
REACTORS
RESEARCH PROGRAMS
SAFETY
SAN ONOFRE-1 REACTOR
SAN ONOFRE-2 REACTOR
SAN ONOFRE-3 REACTOR
THERMAL POWER PLANTS
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WATER MODERATED REACTORS