State trend prediction of spacecraft based on BP neural network

Tianshe Yang, Bin Chen, Hailong Zhang, Xiaole Wang, Yu Gao, Nan Xing
{"title":"State trend prediction of spacecraft based on BP neural network","authors":"Tianshe Yang, Bin Chen, Hailong Zhang, Xiaole Wang, Yu Gao, Nan Xing","doi":"10.1109/MIC.2013.6758086","DOIUrl":null,"url":null,"abstract":"According to the requirement of state trend prediction for spacecraft fault prediction, a spacecraft state trend prediction method is proposed based on BP neural network. The principle and model of BP neural network are introduced into spacecraft fault prediction. Considering the specific application background, the relevant algorithm flow is provided. Taking the temperature parameter of key components in satellite as research object, the state trend prediction computation and comparison are implemented. The precision of the prediction results is evaluated, and it verifies the reliability and validity of the proposed method in quantitative way.","PeriodicalId":404630,"journal":{"name":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","volume":"1150 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIC.2013.6758086","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

According to the requirement of state trend prediction for spacecraft fault prediction, a spacecraft state trend prediction method is proposed based on BP neural network. The principle and model of BP neural network are introduced into spacecraft fault prediction. Considering the specific application background, the relevant algorithm flow is provided. Taking the temperature parameter of key components in satellite as research object, the state trend prediction computation and comparison are implemented. The precision of the prediction results is evaluated, and it verifies the reliability and validity of the proposed method in quantitative way.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于BP神经网络的航天器状态趋势预测
根据航天器故障预测对状态趋势预测的要求,提出了一种基于BP神经网络的航天器状态趋势预测方法。将BP神经网络的原理和模型引入到航天器故障预测中。结合具体的应用背景,给出了相应的算法流程。以卫星关键部件温度参数为研究对象,进行状态趋势预测计算与比较。对预测结果的精度进行了评价,定量地验证了所提方法的可靠性和有效性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Classification of different types of partial discharge based on acoustic emission techniques Economy analysis of extended range electric vehicle in different control strategies An adaptive edge detection algorithm based on gray-scale morphology Internal sorting algorithm for large-scale data based on GPU-assisted Desingn of the heating by planar electromagnetic induction in the power supply
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1