A New Approach for Transient Identification with “Don’t Know” Response Using Neural Networks
In the last years, many different approaches based on neural network (NN) have been proposed for transient identification in nuclear power plants (NPPS). Some of them focus the dynamic identification using recurrent neural networks, however, they are not able to deal with unrecognized transients. Other kind of solution uses competitive learning in order to allow the “don’t know” response. In this case, dynamic features are not well represented.
Unable to display preview. Download preview PDF.
- 1.JEONG E, FURUTA K, KONDO S, “Identification of Transient in Nuclear Power Plant Using Adaptive Template Mtching with Neural Network,” Proceedings of the International Topical Meeting on Nuclear Plant Instrumentation, Control and Human_Machine Interface Technologies, 243–250 (1996)Google Scholar
- 2.LONG B, “Technical Assessment of Disturbance Analysis Systems,” Nuc. Saf., 21,1, 38 (1980).Google Scholar
- 3.BARTLETT EB, UHRIG RE, “Nuclear Power Plant Status Diagnostcs Using an Artificial Neural Network,” Nuclear Technology, Vol. 97, 272 (1992).Google Scholar
- 4.CHEON SW, CHANG SH, “Application of Neural Networks to a Connectionist Expert System for Transient Identification in Nuclear Power Plants,” Nucl. Techol., 102, 177 (1993)Google Scholar
- 5.OHGA Y, SEKI H, “Abnormal transient Identification in Nuclear Power Plants Using Neural Network and Knowledge Processing,” Nucl. Technol., 101, 109 (1993)Google Scholar
- 6.DHANWADA CV, BARTLETT EB, “A New Method for Nuclear Plant Diagnostics Using Neural Networks,” Trans. Am. Nuc. Soc., 66, 116 (1992)Google Scholar
- 7.KIM K, ALJUNDI TL, Bartlett EB, “Confirmation of Artificial Neural Networks: Nuclear Power Plant Fault Diagnostics,” Trans. Am. Nucl. Soc., 66, 112 (1992)Google Scholar
- 8.PARLOS AG et al, “Nonlinear Identification of Process Dynamics Using Neural Networks,” Nucl. Technol.,97, 79 (1993)Google Scholar
- 9.FURUKAWA H, UEDA T, KITAMURA M, “Use of Self-Organizing Neural Networks for Rational Definition of Plant Diagnostic Symptoms,” Proceedings of the International Topical Meeting on Computer-Based Human Support Systems, 441–448 (1995)Google Scholar
- 10.BARTAL Y, LIN J, UHRIG RE, “Nuclear Power Plant Transient Diagnostics Using Artificial Neural Networks that Allow ”Don’t Know“ Classifications,” Nuclear Technology, Vol. 110, (June), 346–449. (1995)Google Scholar
- 11.ROVERSO D, “A Neural Model for Transient Identification in Dynamic Processes.” In: Report HWR-516, OECD HALDEN REACTOR PROJECT, Institutt for Energiteknikk Norway. (1998)Google Scholar
- 12.HAYKIN S, “Neural Networks a Comprehensive Foundation,” 2 ed. Prentice Hall (1999)Google Scholar