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Research on nuclear power fault location method based on info-flow SDG model

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成果类型:
会议论文
作者:
Huang J.;Liu J.;Liu H.;Yang X.;Ma J.
作者机构:
[Huang J.; Liu J.; Yang X.; Ma J.] School of Computer Science, University of South China, Hengyang, Hunan, 421001, China
[Liu H.] School of Electrical Engineering, University of South China, Hengyang, Hunan, 421001, China
语种:
英文
关键词:
Directed graphs;Efficiency;Fault detection;Location;Nuclear fuels;Pressurized water reactors;Coefficients of variations;Faults diagnosis;Flow informations;Information flows;Key word:information flow,information flow SDG model,fault location,coefficient of variation;Key words;Location method;Nuclear accidents;Power faults;Failure analysis
期刊:
ACM International Conference Proceeding Series
年:
2022
卷:
Par F180470
会议名称:
2022 Asia Conference on Electrical, Power and Computer Engineering, EPCE 2022
会议时间:
22 April 2022 through 24 April 2022
出版者:
Association for Computing Machinery
ISBN:
9781450396127
基金类别:
Funded by the State Key Laboratory for Open Projects:SQ-KFKT-24-2021-006
机构署名:
本校为第一机构
院系归属:
电气工程学院
摘要:
Rapid and accurate diagnosis of nuclear accident is the primary link of nuclear emergency. Signed directed graph SDG has good completeness as a common method for fault diagnosis, but the traditional SDG model has low diagnosis efficiency. As a representation method of causal relationship, information flow can be calculated and analyzed from a quantitative point of view, and the application of information flow to causal fault diagnosis can improve the diagnosis efficiency. In this paper, the information flow is introduced to improve the SDG mode...

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