Research on intelligent alarm analysis of nuclear power plant secondary loop system based on multi-level flow model

Due to the intricate and interrelated nature of nuclear power plant systems, any anomaly can trigger a casc ade of alarms. Operators must skillfully assess the system's status amidst this deluge of alarm information and promptly implement appropriate mitigation measures. To address these challenges, an intelligent alarm analysis method based on a Multi-Level Flow Model (MFM) is employed, facilitating the analysis of causal relationships between alarms. Utilizing the secondary loop system and the Low-Pressure Feedwater Heater System (ABP) of a Pressurized Water Reactor (PWR) nuclear power plant as research subjects, a multi-layer flow model for the ABP system was constructed. This model, based on the steady-state operation at full power of the nuclear power plant, clarifies the causal relationships between functions and targets. The mul tilayer flow model was validated using an alarm scenario triggered by an insertion fault superimposed under steady-state operating conditions. The results indicate that the system can filter information, identify root causes, and provide operator s with effective comprehensive diagnostic information. This reduces the impact of a large volume of information on diagnostic tasks and enhances the safety and reliability of nuclear power plant operations.

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Publication Details

Journal
IET conference proceedings.
Published
2025-01-01
DOI
https://doi.org/10.1049/icp.2024.3459
Citations
1
Primary Topic
Fault Detection and Control Systems
Type
article
Field-Weighted Citation Impact
1.21
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article

Research on intelligent alarm analysis of nuclear power plant secondary loop system based on multi-level flow model

Sijuan Chen, Jipu Wang, Fucai Qian, Jian-Hua Chen et al.
1 citations
IET conference proceedings.
Fault Detection and Control Systems
1.21
article

Research on intelligent alarm analysis of nuclear power plant secondary loop system based on multi-level flow model

Sijuan Chen, Jipu Wang, Fucai Qian, Jian-Hua Chen, Chenxi Zhang, Ming Yang
article en
1 citations

Abstract

Due to the intricate and interrelated nature of nuclear power plant systems, any anomaly can trigger a casc ade of alarms. Operators must skillfully assess the system's status amidst this deluge of alarm information and promptly implement appropriate mitigation measures. To address these challenges, an intelligent alarm analysis method based on a Multi-Level Flow Model (MFM) is employed, facilitating the analysis of causal relationships between alarms. Utilizing the secondary loop system and the Low-Pressure Feedwater Heater System (ABP) of a Pressurized Water Reactor (PWR) nuclear power plant as research subjects, a multi-layer flow model for the ABP system was constructed. This model, based on the steady-state operation at full power of the nuclear power plant, clarifies the causal relationships between functions and targets. The mul tilayer flow model was validated using an alarm scenario triggered by an insertion fault superimposed under steady-state operating conditions. The results indicate that the system can filter information, identify root causes, and provide operator s with effective comprehensive diagnostic information. This reduces the impact of a large volume of information on diagnostic tasks and enhances the safety and reliability of nuclear power plant operations.

IET conference proceedings.Vol. 2024(12)
Shenzhen University (CN)
Affordable and clean energy
Openalex Percentile: Top 26%
Fault Detection and Control Systems
1.21
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