A novel wavelet selection scheme for partial discharge signal denoising

Liu, Jiajia and Siew, W.H. and Soraghan, John J. and Morris, Euan A. (2018) A novel wavelet selection scheme for partial discharge signal denoising. In: Conference on Electrical Insulation and Dielectric Phenomena, 2018-10-21 - 2018-10-24, Cancun.

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Abstract

Over the past two decades, wavelet-based techniques have been widely used to extract partial discharge (PD) signals from noisy signals. To effectively select the correct technique to minimize the effect of noise on PD detection, three aspects are considered: wavelet selection, decomposition scale, and noise or threshold estimation. For wavelet selection, popular techniques, including correlation-based wavelet selection scheme (CBWSS) and energy-based wavelet selection scheme (EBWSS), are applied to select an appropriate wavelet basis function. These two schemes, however, have their limitations. CBWSS is not as effective as expected when the signal to noise ratio (SNR) is very low. EBWSS selects the optimal wavelet that can maximize the energy ratio of the PD signal in approximation coefficients through wavelet decomposition. It is not strictly true for damped oscillating PD signals, particularly when the decomposition scale increases. As such, a novel wavelet selection scheme, wavelet entropy-based wavelet selection scheme ( WEBWSS), is proposed to provide an alternative to CBWSS and EBWSS for PD denoising. PD signals are simulated and also obtained through laboratory experiments to demonstrate that this new method has better performance in the removal of noise, particularly when SNR is low.

ORCID iDs

Liu, Jiajia ORCID logoORCID: https://orcid.org/0000-0001-5097-3386, Siew, W.H. ORCID logoORCID: https://orcid.org/0000-0003-4000-6856, Soraghan, John J. ORCID logoORCID: https://orcid.org/0000-0003-4418-7391 and Morris, Euan A. ORCID logoORCID: https://orcid.org/0000-0001-7799-1402;
  • Item type:Conference or Workshop Item(Poster)
    ID code:65117
    Dates:
    Date
    Event
    29 November 2018
    Published
    31 July 2018
    Accepted
    Notes:© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:10 Aug 2018 10:49
    Last modified:11 Nov 2024 16:55
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/65117
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