Enhancement of lightning electric field signals using empirical mode decomposition method

Huo Yuanlian, Qiao Yongfeng
{"title":"Enhancement of lightning electric field signals using empirical mode decomposition method","authors":"Huo Yuanlian, Qiao Yongfeng","doi":"10.1109/ICOT.2014.6956604","DOIUrl":null,"url":null,"abstract":"In this paper, a new lightning electric field signals denoising approach based on noise reduction algorithms in empirical mode decomposition(EMD) which was widely used for analyzing nonlinear and nonstationary data was applied. The data from the simulation and measurements were analyzed to evaluate this method comparing with the traditional FIR low-pass filter. The results showed that the denoising methods based on EMD provides very good results for denoising lightning electric field signals and it was effective and superior to the FIR filter method.","PeriodicalId":343641,"journal":{"name":"2014 International Conference on Orange Technologies","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Orange Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOT.2014.6956604","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

In this paper, a new lightning electric field signals denoising approach based on noise reduction algorithms in empirical mode decomposition(EMD) which was widely used for analyzing nonlinear and nonstationary data was applied. The data from the simulation and measurements were analyzed to evaluate this method comparing with the traditional FIR low-pass filter. The results showed that the denoising methods based on EMD provides very good results for denoising lightning electric field signals and it was effective and superior to the FIR filter method.
利用经验模态分解方法增强雷电电场信号
本文提出了一种基于经验模态分解(EMD)降噪算法的雷电电场信号去噪方法,该方法广泛应用于分析非线性和非平稳数据。通过对仿真和实测数据的分析,将该方法与传统FIR低通滤波器进行比较。结果表明,基于EMD的雷电电场信号去噪方法具有较好的降噪效果,且优于FIR滤波方法。
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
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