Second generation wavelet transform for data denoising in PD measurement

Xiaodi Song, Chengke Zhou, Donald M. Hepburn, Guobin Zhang, M. Michel

    Research output: Contribution to journalArticle

    Abstract

    Detection and diagnosis of partial discharge (PD) activity has been widely adopted in electrical plant condition monitoring. Analysis and detection of PD in practical applications is often hampered by noise in the signal. Recent research has shown that the discrete wavelet transform (DWT) is effective in extracting PD pulses from severe noise. One disadvantage, however, is that DWT does not reproduce accurate PD pulse magnitude and pulse shape after thresholding in the presence of strong noise.

    Original languageEnglish
    Pages (from-to)1531-1537
    Number of pages7
    JournalIEEE Transactions on Dielectrics and Electrical Insulation
    Volume14
    Issue number6
    DOIs
    Publication statusPublished - 1 Dec 2007

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    Partial discharges
    Wavelet transforms
    Discrete wavelet transforms
    Condition monitoring

    Keywords

    • electrical noise
    • wavelet transform
    • PD

    Cite this

    Song, Xiaodi ; Zhou, Chengke ; Hepburn, Donald M. ; Zhang, Guobin ; Michel, M. / Second generation wavelet transform for data denoising in PD measurement. In: IEEE Transactions on Dielectrics and Electrical Insulation. 2007 ; Vol. 14, No. 6. pp. 1531-1537.
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    title = "Second generation wavelet transform for data denoising in PD measurement",
    abstract = "Detection and diagnosis of partial discharge (PD) activity has been widely adopted in electrical plant condition monitoring. Analysis and detection of PD in practical applications is often hampered by noise in the signal. Recent research has shown that the discrete wavelet transform (DWT) is effective in extracting PD pulses from severe noise. One disadvantage, however, is that DWT does not reproduce accurate PD pulse magnitude and pulse shape after thresholding in the presence of strong noise.",
    keywords = "electrical noise, wavelet transform, PD",
    author = "Xiaodi Song and Chengke Zhou and Hepburn, {Donald M.} and Guobin Zhang and M. Michel",
    note = "<p>Originally published in: IEEE Transactions on Dielectrics and Electrical Insulation (2007), 14 (6), pp.1531-1537.</p>",
    year = "2007",
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    Second generation wavelet transform for data denoising in PD measurement. / Song, Xiaodi; Zhou, Chengke; Hepburn, Donald M.; Zhang, Guobin; Michel, M.

    In: IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 14, No. 6, 01.12.2007, p. 1531-1537.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Second generation wavelet transform for data denoising in PD measurement

    AU - Song, Xiaodi

    AU - Zhou, Chengke

    AU - Hepburn, Donald M.

    AU - Zhang, Guobin

    AU - Michel, M.

    N1 - <p>Originally published in: IEEE Transactions on Dielectrics and Electrical Insulation (2007), 14 (6), pp.1531-1537.</p>

    PY - 2007/12/1

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    N2 - Detection and diagnosis of partial discharge (PD) activity has been widely adopted in electrical plant condition monitoring. Analysis and detection of PD in practical applications is often hampered by noise in the signal. Recent research has shown that the discrete wavelet transform (DWT) is effective in extracting PD pulses from severe noise. One disadvantage, however, is that DWT does not reproduce accurate PD pulse magnitude and pulse shape after thresholding in the presence of strong noise.

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    KW - electrical noise

    KW - wavelet transform

    KW - PD

    U2 - 10.1109/TDEI.2007.4401237

    DO - 10.1109/TDEI.2007.4401237

    M3 - Article

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