Performance analysis of wavelet based denoise system for power quality disturbances

The performance analysis of wavelet based denoise system for power quality disturbances including sag, swell, flicker, harmonic, transient and notch is presented in this paper. The denoise algorithm uses Daubechie family wavelet and a universal soft threshold technique applied on the detailed wavele...

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Main Authors: Tan R.H.G., Ramachandaramurthy V.K.
Other Authors: 35325391900
Format: Conference paper
Published: 2023
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spelling my.uniten.dspace-308312023-12-29T15:54:12Z Performance analysis of wavelet based denoise system for power quality disturbances Tan R.H.G. Ramachandaramurthy V.K. 35325391900 6602912020 Daubechie wavelet Denoise Power quality Wavelet transform Discrete wavelet transforms Gaussian noise (electronic) White noise Additive White Gaussian noise Data length Daubechie wavelet Denoise Disturbance signals Excellent performance Inverse discrete wavelet transforms Performance analysis Poor performance Power quality disturbances Soft threshold Standard deviation Wavelet coefficients Wavelet denoise Wavelet analysis The performance analysis of wavelet based denoise system for power quality disturbances including sag, swell, flicker, harmonic, transient and notch is presented in this paper. The denoise algorithm uses Daubechie family wavelet and a universal soft threshold technique applied on the detailed wavelet coefficients based on its standard deviation and data length. This eliminates and reduces the noise content in the signal. Lastly, the inverse discrete wavelet transform is done to reconstruct and recover the denoised PQ disturbance signal. All the disturbance signals are contaminated with Additive White Gaussian Noise of initial noise SNR of 30dB. The wavelet based denoise system in this paper shows excellent performance for sag, swell and flicker, good performance for harmonic, moderate performance for transient and poor performance for notch. The performance analysis presented in this paper provides an understanding of how the power quality disturbance frequency contents and its magnitude effect the performance of the wavelet based denoise system. � 2009 IEEE. Final 2023-12-29T07:54:12Z 2023-12-29T07:54:12Z 2009 Conference paper 10.1109/PTC.2009.5281870 2-s2.0-74949110205 https://www.scopus.com/inward/record.uri?eid=2-s2.0-74949110205&doi=10.1109%2fPTC.2009.5281870&partnerID=40&md5=ce77ae73a772df823d900d118d037f4b https://irepository.uniten.edu.my/handle/123456789/30831 5281870 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Daubechie wavelet
Denoise
Power quality
Wavelet transform
Discrete wavelet transforms
Gaussian noise (electronic)
White noise
Additive White Gaussian noise
Data length
Daubechie wavelet
Denoise
Disturbance signals
Excellent performance
Inverse discrete wavelet transforms
Performance analysis
Poor performance
Power quality disturbances
Soft threshold
Standard deviation
Wavelet coefficients
Wavelet denoise
Wavelet analysis
spellingShingle Daubechie wavelet
Denoise
Power quality
Wavelet transform
Discrete wavelet transforms
Gaussian noise (electronic)
White noise
Additive White Gaussian noise
Data length
Daubechie wavelet
Denoise
Disturbance signals
Excellent performance
Inverse discrete wavelet transforms
Performance analysis
Poor performance
Power quality disturbances
Soft threshold
Standard deviation
Wavelet coefficients
Wavelet denoise
Wavelet analysis
Tan R.H.G.
Ramachandaramurthy V.K.
Performance analysis of wavelet based denoise system for power quality disturbances
description The performance analysis of wavelet based denoise system for power quality disturbances including sag, swell, flicker, harmonic, transient and notch is presented in this paper. The denoise algorithm uses Daubechie family wavelet and a universal soft threshold technique applied on the detailed wavelet coefficients based on its standard deviation and data length. This eliminates and reduces the noise content in the signal. Lastly, the inverse discrete wavelet transform is done to reconstruct and recover the denoised PQ disturbance signal. All the disturbance signals are contaminated with Additive White Gaussian Noise of initial noise SNR of 30dB. The wavelet based denoise system in this paper shows excellent performance for sag, swell and flicker, good performance for harmonic, moderate performance for transient and poor performance for notch. The performance analysis presented in this paper provides an understanding of how the power quality disturbance frequency contents and its magnitude effect the performance of the wavelet based denoise system. � 2009 IEEE.
author2 35325391900
author_facet 35325391900
Tan R.H.G.
Ramachandaramurthy V.K.
format Conference paper
author Tan R.H.G.
Ramachandaramurthy V.K.
author_sort Tan R.H.G.
title Performance analysis of wavelet based denoise system for power quality disturbances
title_short Performance analysis of wavelet based denoise system for power quality disturbances
title_full Performance analysis of wavelet based denoise system for power quality disturbances
title_fullStr Performance analysis of wavelet based denoise system for power quality disturbances
title_full_unstemmed Performance analysis of wavelet based denoise system for power quality disturbances
title_sort performance analysis of wavelet based denoise system for power quality disturbances
publishDate 2023
_version_ 1806427573628960768
score 13.214268