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AuthorHussein, Ramy
AuthorShaban, Khaled Bashir
AuthorEl-Hag, Ayman H.
Available date2022-12-21T10:01:45Z
Publication Date2015
Publication NameAnnual Report - Conference on Electrical Insulation and Dielectric Phenomena, CEIDP
ResourceScopus
URIhttp://dx.doi.org/10.1109/CEIDP.2015.7352003
URIhttp://hdl.handle.net/10576/37489
AbstractMeasuring partial discharge (PD) phenomena in power transformers is often conducted by acoustic emission (AE) method. However, many interference sources are usually encountered with the captured PD signals which negatively affect the PD detection and classification. Thus, an effective and efficient denoising technique is required to suppress such environmental noises. Most denoising attempts aim to address additive white Gaussian noise, which is considered the main ambient interference source coupling with PD signals through data acquisition process. In this paper, we propose a power spectral subtraction denoising (PSSD) method and examine its denoising performance in the presence of modest and severe noise levels. The simulation results verify that PSSD has superior denoising performance when compared to one of the conventional wavelet shrinkage denoising methods. Four evaluation metrics are utilized to confirm the superiority of PSSD: signal-to-noise ratio, root mean square error, cross-correlation coefficient, and reduction in noise level. 2015 IEEE.
SponsorQatar National Research Fund
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Subjectacoustic emissions signal
interference suppression
Partial discharge
power spectral subtraction denoising
signal-to-noise ratio
wavelet-based denoising
white Gaussian noise
TitleAcoustic partial discharge signal denoising using power spectral subtraction
TypeConference Paper
Pagination330-333
Volume Number2015-December
dc.accessType Abstract Only


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