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A Denoising Method of Partial Discharge Signal Based on Improved SVD-VMD

Zhipeng Lei, Feiyu Wang, Chuanyang Li

2023IEEE Transactions on Dielectrics and Electrical Insulation60 citationsDOI

Abstract

A denoising method combined with singular value decomposition (SVD) and variational mode decomposition (VMD) is proposed to eliminate noise in on-site partial discharge (PD) signals from high-voltage electrical equipment. In the Fourier transform power spectrum, periodic narrowband interference was eliminated after SVD was offered to determine the number of singular values of periodic narrowband interference. Then, the PD signal was decomposed into <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> intrinsic mode function (IMF) components by VMD. The empirical mode decomposition (EMD) method was used to determine the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> value of white noise’s IMF components. An improved <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3\sigma $ </tex-math></inline-formula> criterion threshold method was proposed to eliminate the residual noise in the PD signal. The denoising method was compared with the other two methods to analyze the denoising effect on the simulation and experimental PD signal. This article’s denoising method can eliminate periodic narrowband interference and white noise in different PD signals of cavity discharge, corona discharge, and those from the motors’ coil. The denoised PD pulse waveform has a higher signal-to-noise ratio (SNR) and normalized correlation coefficient (NCC) and a lower mean square error (mse), indicating that the waveform’s original characteristic remains.

Topics & Concepts

Noise reductionPartial dischargeSIGNAL (programming language)AcousticsMaterials scienceSingular value decompositionComputer scienceElectronic engineeringAnalytical Chemistry (journal)AlgorithmChemistryPhysicsElectrical engineeringChromatographyEngineeringVoltageProgramming languageImage and Signal Denoising MethodsAdvanced Sensor and Control SystemsMachine Fault Diagnosis Techniques
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