Journal
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Volume 67, Issue 10, Pages 2262-2272Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2018.2816438
Keywords
Denoising; partial discharge (PD); singular value decomposition (SVD); wavelet transform
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Denoising is a key step in diagnosis and evaluation of partial discharge (PD) signals in power transformers. In this paper, a new PD signal denoising algorithm is presented, which is based on the combination of dual-tree complex wavelet transform (DTCWT) and adaptive singular value decomposition (ASVD). This new algorithm, which is introduced as adaptive DTCWT (ADTCWT), was evaluated through simulations and experimental tests. ADTCWT was employed in denoising from PD signals based on the selection of best singular values in each DTCWT level decomposition, corresponding to PD signal and noise. The superior performance of the ADTCWT algorithm was demonstrated using various indices in comparison with those of DTCWT and ASVD methods in noise reduction, besides preserving time of arrival of PD signals and PD localization.
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