Fault detection for nuclear power plant based on improved moving window and sparse autoencoder

IF 2.3 3区 工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY
Shaomin Zhu , Wenzhe Yin , Hong Xia
{"title":"Fault detection for nuclear power plant based on improved moving window and sparse autoencoder","authors":"Shaomin Zhu ,&nbsp;Wenzhe Yin ,&nbsp;Hong Xia","doi":"10.1016/j.anucene.2025.111626","DOIUrl":null,"url":null,"abstract":"<div><div>Due to factors such as component performance degradation and changes in operating conditions, nuclear power plants (NPPs) equipment exhibits significant time-varying characteristics during operation, leading to the failure of fault detection models. Therefore, this study proposes a fault detection method based on an improved moving window and sparse autoencoder to enhance the adaptability of the detection method to the time-varying data of NPPs. This method establishes a sparse autoencoder as a fault detection model, determining the operating status of equipment by calculating the statistical relationship between test data and reconstructed data. In this process, the traditional moving window update strategy is optimized based on Euclidean distance, and the improved moving window strategy enables effective model updating. Finally, the effectiveness of the proposed method is verified using data from a nuclear power plant reactor coolant pump. The results show that the proposed method performs well in terms of fault detection rate and false alarm rate.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"222 ","pages":"Article 111626"},"PeriodicalIF":2.3000,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Nuclear Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306454925004438","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NUCLEAR SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Due to factors such as component performance degradation and changes in operating conditions, nuclear power plants (NPPs) equipment exhibits significant time-varying characteristics during operation, leading to the failure of fault detection models. Therefore, this study proposes a fault detection method based on an improved moving window and sparse autoencoder to enhance the adaptability of the detection method to the time-varying data of NPPs. This method establishes a sparse autoencoder as a fault detection model, determining the operating status of equipment by calculating the statistical relationship between test data and reconstructed data. In this process, the traditional moving window update strategy is optimized based on Euclidean distance, and the improved moving window strategy enables effective model updating. Finally, the effectiveness of the proposed method is verified using data from a nuclear power plant reactor coolant pump. The results show that the proposed method performs well in terms of fault detection rate and false alarm rate.
基于改进运动窗和稀疏自编码器的核电厂故障检测
由于部件性能退化和运行工况变化等因素,核电站设备在运行过程中表现出明显的时变特征,导致故障检测模型失效。因此,本研究提出了一种基于改进的移动窗和稀疏自编码器的故障检测方法,以增强检测方法对核电厂时变数据的适应性。该方法建立稀疏自编码器作为故障检测模型,通过计算测试数据与重构数据之间的统计关系来确定设备的运行状态。在此过程中,对传统的基于欧氏距离的移动窗口更新策略进行了优化,改进的移动窗口策略实现了有效的模型更新。最后,用某核电站反应堆冷却剂泵的实测数据验证了该方法的有效性。结果表明,该方法在故障检测率和虚警率方面都有较好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Annals of Nuclear Energy
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信