scholarly journals Novel noise reduction method based on improved empirical wavelet transform and kurtosis for partial discharge signal of high-voltage cables

2020 ◽  
Vol 2020 (11) ◽  
pp. 1088-1094
Author(s):  
Xinghe Ma ◽  
Dengkui Zhang ◽  
Ying Zhang
Keyword(s):  
Wavelet Transform ◽  
Noise Reduction ◽  
High Voltage ◽  
Reduction Method ◽  
Partial Discharge ◽  
Empirical Wavelet Transform

scholarly journals Denoising of Heavily Contaminated Partial Discharge signals in High-Voltage Cables Using Maximal Overlap Discrete Wavelet Transform

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6540
Author(s):  
Mohammed A. Shams ◽  
Hussein I. Anis ◽  
Mohammed El-Shahat
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
High Voltage ◽  
Signal To Noise Ratio ◽  
Partial Discharge ◽  
Gaussian White Noise ◽  
Discrete Wavelet ◽  
Power Cable ◽  
Power Cables ◽  
Algorithm Performance

Online detection of partial discharges (PD) is imperative for condition monitoring of high voltage equipment as well as power cables. However, heavily contaminated sites often burden the signals with various types of noise that can be challenging to remove (denoise). This paper proposes an algorithm based on the maximal overlap discrete wavelet transform (MODWT) to denoise PD signals originating from defects in power cables contaminated with various levels of noises. The three most common noise types, namely, Gaussian white noise (GWN), discrete spectral interference (DSI), and stochastic pulse shaped interference (SPI) are considered. The algorithm is applied to an experimentally acquired void-produced partial discharge in a power cable. The MODWT-based algorithm achieved a good improvement in the signal-to-noise ratio (SNR) and in the normalized correlation coefficient (NCC) for the three types of noises. The MODWT-based algorithm performance was also compared to that of the empirical Bayesian wavelet transform (EBWT) algorithm, in which the former showed superior results in denoising SPI and DSI, as well as comparable results in denoising GWN. Finally, the algorithm performance was tested on a PD signal contaminated with the three type of noises simultaneously in which the results were also superior.

scholarly journals Measurement and Denoising of Partial Discharge Signal in High Voltage Cables using Wavelet Transform

2019 ◽  
Vol 9 (2) ◽  
pp. 2461-2468
Keyword(s):  
Wavelet Transform ◽  
High Voltage ◽  
Partial Discharge ◽  
Reconstruction Error ◽  
Underground Cables ◽  
The Past ◽  
Error Ratio ◽  
Different Types ◽  
Hv Cable

A huge amount of exploration propagated over the past decade investigates the characterization of Partial Discharge (PD) inception in cable ideology. Underground cables are passed down as surrogate for over hauling in congested areas. The intention of this research is to examine the feasibility of exploring insulation defects present in High Voltage (HV) Cable setup by employing PD disclosure under alternating current (AC) Voltage. Study of PD characteristics has a congregate of predictable distinguished contraption to prove the probity and the affirmation of electrical insulation of Power System. In this work, the cable is exposed into the measurement of PD signal under artificially conceived defects. PD signal parameters are mainly depends on the size of void and applied voltage. In general, the measured PD signal is depraved with interferences. To identify the exact characteristics of PD distinctive and its severity, the PD signal is subjected to Wavelet Transform (WT) for denoising. Different types of WT families with various level is used for de-noising. To identify the effectiveness of the WT for de-noising guidelines like Signal to Reconstruction Error Ratio (SRER) and Reduction in Noise Level (RNL) are used.

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