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AuthorHussein, Ramy
AuthorBashirShaban, Khaled
AuthorEl-Hag, Ayman H.
Available date2021-09-01T10:03:29Z
Publication Date2016
Publication NameIEEE Transactions on Dielectrics and Electrical Insulation
ResourceScopus
URIhttp://dx.doi.org/10.1109/TDEI.2015.005532
URIhttp://hdl.handle.net/10576/22468
AbstractPower transformers are one of the most important and expensive electrical equipment that require online condition monitoring. Partial discharge (PD) measurement is considered the most effective and non-destructive approach to observe the condition of power transformers in service. However, many sources of noise interfere with the captured PD signals leading to waveform deformation. Thus, it is important for the detection and classification of PD signals to initially suppress the noise encountered with PD measurement. In this paper, we investigate a method, named power spectral subtraction denoising (PSSD) that uses fast Fourier transform to restrain the random noise encountered in measured acoustic PD signals. The denoising performance of PSSD is compared with those of wavelet-based denoising techniques in addition to the mathematical morphological filter. The denoising techniques are first examined on PD signals contaminated with low and high levels of simulated random noise. The denoising evaluation metrics show the superiority of PSSD over the other techniques. Moreover, a modified PSSD (M-PSSD) method is presented to address the actual PD signals corrupted with real random noise. High reduction in noise levels are achieved using M-PSSD. 2016 IEEE.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectAcoustic noise
Condition monitoring
Fast Fourier transforms
Mathematical morphology
Partial discharges
Power transformers
Spectrum analysis
Wavelet analysis
De-noising
De-noising techniques
Morphological filters
Noise power spectrum estimations
Online condition monitoring
Partial discharge measurements
Partial discharge signal
Random noise
Signal denoising
TitleDenoising of acoustic partial discharge signals corrupted with random noise
TypeArticle
Pagination1453-1459
Issue Number3
Volume Number23
dc.accessType Abstract Only


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