Research on Fault Diagnosis Method for Reactor Primary Circuit System Based on multi-source information fusion
Authors: 
Jie Ma, Zhuang Han, Qiao PengAuthors Info & Claims
Pages 402 - 408
Abstract
Reactor primary circuit system is a complex dynamic system, variable parameter coupling, operation safety problems are prominent. In order to reduce the risk, a multi-source information fusion diagnosis system based on signed directed graph (SDG) and particle swarm optimization BP neural network (PSO-BP) is proposed. Utilizing D-S evidence theory for neural network diagnostic information fusion, logic inference combining SDG model, to determine potential failure. Simulation test shows that the intelligent diagnosis model could estimate the faults effectively, and provides the fault alarm transmission path.
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Published In
October 2022
753 pages
ISBN:9781450397780
DOI:10.1145/3569966
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Association for Computing Machinery
New York, NY, United States
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Published: 20 December 2022
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- Refereed limited
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CSSE 2022
CSSE 2022: 2022 5th International Conference on Computer Science and Software Engineering
October 21 - 23, 2022
Guilin, China
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Overall Acceptance Rate 33 of 74 submissions, 45%
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