基于 KPCA 的核电站化学和容积控制系统故障检测和诊断模型

IF 1.9 3区工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY

Annals of Nuclear Energy Pub Date : 2024-10-19 DOI:10.1016/j.anucene.2024.110973

Yiqian Sun , Meiqi Song , Chunjing Song , Meng Zhao , Yanhua Yang

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引用次数: 0

摘要

为研究核电站系统故障智能检测与诊断方法，提高核电站化学与容积控制系统（CVS）内部故障的检测与诊断效果，本研究提出了核电站化学与容积控制系统（FDD-CVS）智能故障检测与诊断模型。该模型基于 CVS 系统的故障模式和效应分析，通过将核主成分分析（KPCA）与决策树和支持向量机（SVM）相结合来实现。FDD-CVS 可根据独立的时间点系统参数快速、直观地识别 CVS 中的故障，并能诊断故障类型和具体故障位置。该模型具有原理清晰、分层诊断、诊断速度快和结果可视化等特点。利用被动核电模拟分析仪的数据对模型进行了训练和测试。FDD-CVS 的故障检测率为 96.38%，误报率为 4.34%，平均准确率为 98.40%。总之，本文提出的故障监测与诊断方法具有创新性，为核电站的故障诊断研究提供了有价值的参考。

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KPCA-based fault detection and diagnosis model for the chemical and volume control system in nuclear power plants

To study the fault intelligent detection and diagnosis method of nuclear power plant systems and improve the detection and diagnosis effect of internal fault of nuclear power plant Chemical and Volume control System (CVS), this study presents an intelligent Fault Detection and Diagnosis model for the Chemical and Volume control System (FDD-CVS) in nuclear power plants (NPPs). The model is based on failure mode and effects analysis of the CVS system and is implemented by combining kernel principal component analysis (KPCA) with decision tree and support vector machine (SVM). FDD-CVS can rapidly and visually recognize faults in CVS based on independent time-point system parameters, and it is capable of diagnosing fault types and specific fault locations. The model is characterized by clear principles, hierarchical diagnostics, fast diagnostic speed, and visualized results. The model is trained and tested by using the data of the passive nuclear power simulation analyzer. The fault detection rate of FDD-CVS is 96.38%, the false alarm rate is 4.34%, and the average accuracy rate is 98.40%. Overall, the fault monitoring and diagnostic method proposed in this article is innovative and provides valuable references for fault diagnosis research in nuclear power plants.

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来源期刊

Annals of Nuclear Energy 工程技术-核科学技术

CiteScore

4.30

自引率

21.10%

发文量

632

审稿时长

7.3 months

期刊介绍： Annals of Nuclear Energy provides an international medium for the communication of original research, ideas and developments in all areas of the field of nuclear energy science and technology. Its scope embraces nuclear fuel reserves, fuel cycles and cost, materials, processing, system and component technology (fission only), design and optimization, direct conversion of nuclear energy sources, environmental control, reactor physics, heat transfer and fluid dynamics, structural analysis, fuel management, future developments, nuclear fuel and safety, nuclear aerosol, neutron physics, computer technology (both software and hardware), risk assessment, radioactive waste disposal and reactor thermal hydraulics. Papers submitted to Annals need to demonstrate a clear link to nuclear power generation/nuclear engineering. Papers which deal with pure nuclear physics, pure health physics, imaging, or attenuation and shielding properties of concretes and various geological materials are not within the scope of the journal. Also, papers that deal with policy or economics are not within the scope of the journal.