Fusion of multi-frequency eddy current signals-by using wavelet analysis method

L. Q. Li, K. Tsukada, K. Hanasaki, Zheng Liu
{"title":"Fusion of multi-frequency eddy current signals-by using wavelet analysis method","authors":"L. Q. Li, K. Tsukada, K. Hanasaki, Zheng Liu","doi":"10.1109/ICIF.2002.1021138","DOIUrl":null,"url":null,"abstract":"This paper presents a novel scheme to fuse one-dimensional multi-frequency eddy current signals by using multiresolution discrete wavelet analysis method. This technique consists of three steps. First, raw signals are preprocessed and decomposed into approximations and details at different resolution levels. The discrete wavelet transform is adopted at this stage. Then, several fusion processes are implemented in the coefficients domain. Finally, the inverse discrete wavelet transform is achieved to get the fusion result. In this technique, we develop a new mask-signal-modulated fusion algorithm to fuse in coefficients domain. It is performed and compared with other fusion methods based on the criteria of signal-to-noise ratio of the fused result. From our experiments, it demonstrates a better performance and shows a promising application on the two-dimensional multi-frequency eddy current signals.","PeriodicalId":399150,"journal":{"name":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIF.2002.1021138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

This paper presents a novel scheme to fuse one-dimensional multi-frequency eddy current signals by using multiresolution discrete wavelet analysis method. This technique consists of three steps. First, raw signals are preprocessed and decomposed into approximations and details at different resolution levels. The discrete wavelet transform is adopted at this stage. Then, several fusion processes are implemented in the coefficients domain. Finally, the inverse discrete wavelet transform is achieved to get the fusion result. In this technique, we develop a new mask-signal-modulated fusion algorithm to fuse in coefficients domain. It is performed and compared with other fusion methods based on the criteria of signal-to-noise ratio of the fused result. From our experiments, it demonstrates a better performance and shows a promising application on the two-dimensional multi-frequency eddy current signals.
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
利用小波分析方法对多频涡流信号进行融合
提出了一种利用多分辨率离散小波分析方法融合一维多频涡流信号的新方案。这个技巧包括三个步骤。首先,对原始信号进行预处理,并将其分解为不同分辨率下的近似值和细节。这一阶段采用离散小波变换。然后,在系数域中实现若干融合处理。最后,通过离散小波逆变换得到融合结果。在该技术中,我们提出了一种新的掩模信号调制融合算法,用于系数域的融合。以融合结果的信噪比为准则,对该方法进行了验证,并与其他融合方法进行了比较。实验结果表明,该方法具有较好的性能,在二维多频涡流信号处理中具有广阔的应用前景。
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
Approximating fuzzy measures by hierarchically decomposable ones Tracking and fusion for wireless sensor networks A dynamic communication model for loosely coupled hybrid tracking systems On platform-based sensor management An improved Bayes fusion algorithm with the Parzen window method
×
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