A pattern recognition approach based on DTW for automatic transient identification in nuclear power plants

被引:21
作者
Galbally, Javier [1 ]
Galbally, David [2 ]
机构
[1] Univ Autonoma Madrid, EPS, Biometr Recognit Grp ATVS, E-28049 Madrid, Spain
[2] Innomerics, Pozuelo De Alarcon 28223, Spain
关键词
Transient identification; Nuclear power plants; Components fatigue; Pattern recognition; Dynamic time warping; OPTIMIZATION; MODEL;
D O I
10.1016/j.anucene.2015.03.003
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
Automatic identification of transients in nuclear power plants (NPPs) allows monitoring the fatigue damage accumulated by critical components during plant operation, and is therefore of great importance for ensuring that usage factors remain within the original design bases postulated by the plant designer. Although several schemes to address this important issue have been explored in the literature, there is still no definitive solution available. In the present work, a new method for automatic transient identification is proposed, based on the Dynamic Time Warping (DTW) algorithm, largely used in other related areas such as signature or speech recognition. The novel transient identification system is evaluated on real operational data following a rigorous patterb recognition protocol. Results show the high accuracy of the proposed approach, which is combined with other interesting features such as its low complexity and its very limited requirements of training data. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:287 / 300
页数:14
相关论文
共 22 条
[1]  
ASME, 2013, Boiler and pressure vessel code
[2]   DYNAMIC PROGRAMMING [J].
BELLMAN, R .
SCIENCE, 1966, 153 (3731) :34-&
[3]  
Bellman R., 1959, P IRE, V4, P1, DOI 10.1109/TAC.1959.1104847
[4]  
Bishop Christopher, 2006, Pattern Recognition and Machine Learning, DOI 10.1117/1.2819119
[5]  
Brummer N., 2007, Focal multi-class: Toolkit for evaluation, fusion and calibration of multi-class recognition scorestutorial and user manual
[6]   Identification of nuclear power plant transients using the Particle Swarm Optimization algorithm [J].
Carlos Canedo Medeiros, Jose Antonio ;
Schirru, Roberto .
ANNALS OF NUCLEAR ENERGY, 2008, 35 (04) :576-582
[7]   CEPSTRAL ANALYSIS TECHNIQUE FOR AUTOMATIC SPEAKER VERIFICATION [J].
FURUI, S .
IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING, 1981, 29 (02) :254-272
[8]   Feasibility study on transient identification in nuclear power plants using support vector machines [J].
Gottlieb, Christoffer ;
Arzhanov, Vasily ;
Gudowski, Waclaw ;
Garis, Ninos .
NUCLEAR TECHNOLOGY, 2006, 155 (01) :67-77
[9]   MINIMUM PREDICTION RESIDUAL PRINCIPLE APPLIED TO SPEECH RECOGNITION [J].
ITAKURA, F .
IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING, 1975, AS23 (01) :67-72
[10]   Feature selection: Evaluation, application, and small sample performance [J].
Jain, A ;
Zongker, D .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1997, 19 (02) :153-158