Fault Diagnosis Method of Link Control System for Gravitational Wave Detection

IF 1.9 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS
Ai Gao, Shengnan Xu, Zichen Zhao, Haibin Shang, Rui Xu
{"title":"Fault Diagnosis Method of Link Control System for Gravitational Wave Detection","authors":"Ai Gao, Shengnan Xu, Zichen Zhao, Haibin Shang, Rui Xu","doi":"10.23919/jsee.2024.000048","DOIUrl":null,"url":null,"abstract":"To maintain the stability of the inter-satellite link for gravitational wave detection, an intelligent learning monitoring and fast warning method of the inter-satellite link control system failure is proposed. Different from the traditional fault diagnosis optimization algorithms, the fault intelligent learning method proposed in this paper is able to quickly identify the faults of inter-satellite link control system despite the existence of strong coupling nonlinearity. By constructing a two-layer learning network, the method enables efficient joint diagnosis of fault areas and fault parameters. The simulation results show that the average identification time of the system fault area and fault parameters is 0.27 s, and the fault diagnosis efficiency is improved by 99.8% compared with the traditional algorithm.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"30 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Systems Engineering and Electronics","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.23919/jsee.2024.000048","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

To maintain the stability of the inter-satellite link for gravitational wave detection, an intelligent learning monitoring and fast warning method of the inter-satellite link control system failure is proposed. Different from the traditional fault diagnosis optimization algorithms, the fault intelligent learning method proposed in this paper is able to quickly identify the faults of inter-satellite link control system despite the existence of strong coupling nonlinearity. By constructing a two-layer learning network, the method enables efficient joint diagnosis of fault areas and fault parameters. The simulation results show that the average identification time of the system fault area and fault parameters is 0.27 s, and the fault diagnosis efficiency is improved by 99.8% compared with the traditional algorithm.
引力波探测链路控制系统的故障诊断方法
为了保持引力波探测卫星间链路的稳定性,本文提出了一种卫星间链路控制系统故障智能学习监测与快速预警方法。与传统的故障诊断优化算法不同,本文提出的故障智能学习方法能够在存在强耦合非线性的情况下快速识别卫星间链路控制系统的故障。通过构建双层学习网络,该方法实现了对故障区域和故障参数的高效联合诊断。仿真结果表明,系统故障区域和故障参数的平均识别时间为 0.27 s,与传统算法相比,故障诊断效率提高了 99.8%。
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
Journal of Systems Engineering and Electronics
Journal of Systems Engineering and Electronics 工程技术-工程:电子与电气
CiteScore
4.10
自引率
14.30%
发文量
131
审稿时长
7.5 months
期刊介绍: Information not localized
×
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:481959085
Book学术官方微信