Research on fault diagnosis methods for the reactor coolant system of nuclear power plant based on D-S evidence theory

被引:104
作者
Gong, Yongjian [1 ]
Su, Xiaoyan [1 ]
Qian, Hong [1 ]
Yang, Ning [1 ]
机构
[1] Shanghai Univ Elect Power, Sch Automat Engn, Shanghai 200090, Peoples R China
基金
中国国家自然科学基金;
关键词
Nuclear power plant; Main coolant system; Fault diagnosis; D-S evidence theory; Triangle fuzzy function; DEPENDENCE ASSESSMENT; DATA FUSION;
D O I
10.1016/j.anucene.2017.10.026
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
Great attention is paid to nuclear safety which occupies the key position in the development of nuclear power plant. At present, nuclear industry is in a momentous period of strategic opportunities for development in China. Fault diagnosis systems are widely applied to guarantee the safety of nuclear power plants, and how to improve their quality is vital. D-S evidence theory has been used widely in fault diagnosis due to its effectiveness and flexibility in dealing with uncertain and subjective information. In this paper, a new fault diagnosis method for the main coolant system of nuclear power plant based on D-S evidence theory is presented. Firstly, a triangle fuzzy function is built according to historical data of the symptoms. Secondly, the basic probability assignment functions (BPAs) are constructed based on the triangle fuzzy function of symptoms and the relationship between symptoms and faults. Finally, Dempster's combination rule is used to gain the fused BPA for decision. Examples of typical fault diagnosis in the main coolant system of a nuclear power plant are illustrated to show the use and effectiveness of the proposed method. The results demonstrate that the proposed model can not only get more accurate judgments under some cases, but also provide flexibility in dealing with uncertain information. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:395 / 399
页数:5
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