A hybrid neural network---fuzzy logic approach to nuclear power plant transient identification
- Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering
- Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering Oak Ridge National Lab., TN (United States)
A methodology is presented that couples pretrained artificial neural networks (ANNs) to rule-based fuzzy logic systems, for the purpose of distinguishing different transients in a Nuclear Power Plant (NPP). A model referenced approach is utilized in order to provide timely concise and task specific information about the status of the system under consideration. A rule based system integrated with a set of neural networks, that typify steady-state operation as well as different transients, diagnoses the state of the system and identifies the type of transient under development. ANNs produce their response in the form of membership functions which independently represent individual transients and the steady-state. Membership functions condense functionally relevant information in order for the overall system to successfully perform transient identification, in a time span faster or at least comparable to that of the transient development. To demonstrate the proposed methodology simulated accidents corresponding to a particular category of transients are used. The results obtained demonstrate the excellent noise tolerance of the ANNs and suggest a new approach for transient identification within the framework of fuzzy logic.
- Research Organization:
- Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering; Oak Ridge National Lab., TN (United States)
- Sponsoring Organization:
- USDOE; USDOE, Washington, DC (United States)
- DOE Contract Number:
- FG07-88ER12824; AC05-84OR21400
- OSTI ID:
- 6682378
- Report Number(s):
- CONF-9109110-13; ON: DE93003558
- Resource Relation:
- Conference: International conference on frontiers in innovative computing for the nuclear industry, Jackson, WY (United States), 15-18 Sep 1991
- Country of Publication:
- United States
- Language:
- English
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Fuzzy logic -- artificial neural networks integration for transient identification
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Related Subjects
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
NUCLEAR POWER PLANTS
REACTOR MONITORING SYSTEMS
FUZZY LOGIC
NEURAL NETWORKS
COMPUTERIZED SIMULATION
DECISION MAKING
SIGNAL CONDITIONING
SIGNALS
TRANSIENTS
MATHEMATICAL LOGIC
NUCLEAR FACILITIES
POWER PLANTS
SIMULATION
THERMAL POWER PLANTS
220400* - Nuclear Reactor Technology- Control Systems
220900 - Nuclear Reactor Technology- Reactor Safety
990200 - Mathematics & Computers