Linear Representation and Sparse Solution for Transient Identification in Nuclear Power Plants
作者： Yuan Chang , Xiaojin Huang , Yi Hao , Chun-Wen Li
关键词: Linear space 、 Engineering 、 Nuclear power plant 、 Modular design 、 Control engineering 、 Norm (mathematics) 、 Singular value decomposition 、 Linear representation 、 Linear combination 、 Nuclear power 、 Control theory
摘要: For the safe operation of nuclear power plants (NPPs), it is significant to promptly and correctly identify malfunctions/transients, which difficult for operators by monitoring variation important parameters. In this paper, a novel method proposed transient identification in NPPs. It directly models transients linear space that represented matrix instead training process. Then can be via combination columns modeling matrix, coefficient vector encodes identity transient. To obtain vector, smoothed l0 -norm optimization (SL0) algorithm adopted, where truncated singular value decomposition (TSVD) combined improve stability. accomplished examining property solution using three quantities. The classify successfully reject “unknown” types, applicable under wide range operational conditions. verified simulator data pebble-bed modular high temperature gas-cooled reactor plant (HTR-PM) developed Institute Nuclear New Energy Technology with Tsinghua University.
harvard.edu
sci-hub.se 参考文章(40)
Yair Bartal, Jie Lin, Robert E. Uhrig, Nuclear power plant transient diagnostics using artificial neural networks that allow 'don't-know' classifications Nuclear Technology. ,vol. 110, pp. 436- 449 ,(1995) , 10.13182/NT95-A35112
Young-Gyu No, Ju-Hyun Kim, Man-Gyun Na, Dong-Hyuk Lim, Kwang-Il Ahn, MONITORING SEVERE ACCIDENTS USING AI TECHNIQUES Nuclear Engineering and Technology. ,vol. 44, pp. 393- 404 ,(2012) , 10.5516/NET.04.2012.512
Antônio C.de A. Mol, Aquilino S. Martinez, Roberto Schirru, A neural model for transient identification in dynamic processes with “don't know” response Annals of Nuclear Energy. ,vol. 30, pp. 1365- 1381 ,(2003) , 10.1016/S0306-4549(03)00072-0
Dongliyu, Zhou zhiwei, Sui zhe, Ma Yuanle, Zhou Shuyong, Simulation for the Secondary Loop of the Chinese 200Mwe HTR-PM Base on Vpower Energy Procedia. ,vol. 16, pp. 1831- 1838 ,(2012) , 10.1016/J.EGYPRO.2012.01.281
Rafael Gomes da Costa, Antônio Carlos de Abreu Mol, Paulo Victor R. de Carvalho, Celso Marcelo Franklin Lapa, An efficient Neuro-Fuzzy approach to nuclear power plant transient identification Annals of Nuclear Energy. ,vol. 38, pp. 1418- 1426 ,(2011) , 10.1016/J.ANUCENE.2011.01.027
Davide Roverso, Plant diagnostics by transient classification: The ALADDIN approach International Journal of Intelligent Systems. ,vol. 17, pp. 767- 790 ,(2002) , 10.1002/INT.10049
G. Hosein Mohimani, Massoud Babaie-Zadeh, Christian Jutten, Fast Sparse Representation Based on Smoothed ℓ0 Norm Independent Component Analysis and Signal Separation. pp. 389- 396 ,(2007) , 10.1007/978-3-540-74494-8_49
T.V. Santosh, A. Srivastava, V.V.S. Sanyasi Rao, A.K. Ghosh, H.S. Kushwaha, Diagnostic system for identification of accident scenarios in nuclear power plants using artificial neural networks Reliability Engineering & System Safety. ,vol. 94, pp. 759- 762 ,(2009) , 10.1016/J.RESS.2008.08.005
E. Zio, P. Baraldi, Evolutionary fuzzy clustering for the Classification of transients in nuclear components Progress in Nuclear Energy. ,vol. 46, pp. 282- 296 ,(2005) , 10.1016/J.PNUCENE.2005.03.010
Davide Roverso, Soft computing tools for transient classification soft computing. ,vol. 127, pp. 137- 156 ,(2000) , 10.1016/S0020-0255(00)00035-9