基于BP神经网络的航天器状态趋势预测

Tianshe Yang, Bin Chen, Hailong Zhang, Xiaole Wang, Yu Gao, Nan Xing
{"title":"基于BP神经网络的航天器状态趋势预测","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":"{\"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}","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

摘要

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。
State trend prediction of spacecraft based on BP neural network
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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