Research on Conducted EMI Noise Diagnosis Method based on Infomax-WT Algorithm

Research on Conducted EMI Noise Diagnosis Method based on Infomax-WT Algorithm

baitong_song

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Baitong Song

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Wu Zhang

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Zhou Chen

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Hao Ma

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Yakang Pei

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1 Nanjing Normal University

GJSFR Volume 20 Issue A13

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In this paper, a diagnostic method of conducted EMI noise based on the Infomax-WT algorithm is proposed. Using collected conductive EMI noise samples, several independent noise signals are separated by Infomax. Each noise signal is subjected to wavelet transform to obtain the time-frequency diagram of each noise signal. The noise source is determined according to the frequency characteristic obtained by the time-frequency chart. Finally.

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References

Song Zhenfei,Su Donglin,Xie Shuguo (2009). Detecting the Number of EMI Sources Based on Higher Order Statistics.
Zhang Wenfa (2008). A denoising adaptive blind separation algorithm based on Infomax.
Wu Xiaopei,Ye Zhongfu,Zhang Shen Qian,Daoxin (2005). On-line Infomax algorithm and its application in long recording EEG de-noising.
Deng Feiyue (2016). Research on feature extraction and diagnosis method of rolling bearing fault.
Yuan Shang Haikun,Wang Jinsha,Jin Yu,Song (2014). Partial discharge feature extraction based on cross wavelet transform and correlation coefficient matrix.
Duan Chendong,Gao Qiang,Xu Xianfeng (2013). The application of frequency slice wavelet transform time-frequency analysis method in the fault diagnosis of generator set.
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Ge Zhizhi,Chen Zhongsheng (2006). Time-frequency analysis technology of Matlab and its application.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

baitong_song. 2020. \u201cResearch on Conducted EMI Noise Diagnosis Method based on Infomax-WT Algorithm\u201d. Global Journal of Science Frontier Research - A: Physics & Space Science GJSFR-A Volume 20 (GJSFR Volume 20 Issue A13): .

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GJSFR Volume 20 Issue A13
Pg. 59- 64

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Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

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GJSFR-A Classification: FOR Code: 091301p

Submission ReceivedNovember 18, 2020
RevisedNovember 18, 2020
Peer Review Double Blind
Handling Editor
Accepted November 24, 2020
Published December 14, 2020

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v1.2

Issue date

December 14, 2020

Language

English

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