Power quality disturbance magnitude characterization using wavelet transformation analysis part 1-theory

In this paper, a few approaches to detect, localize, and investigate the feasibility of classifying various types of power quality disturbances are presented. The approaches are based on wavelet transform analysis, particularly the Paul, Gaussian, and Daubechies wavelet transform. The key idea under...

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Main Authors: Zin, A.A.M, Goh, H.H, Lo, Kueiming Lun
Format: Article
Published: Elsevier Ltd. 2008
Subjects:
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author Zin, A.A.M
Goh, H.H
Lo, Kueiming Lun
author_facet Zin, A.A.M
Goh, H.H
Lo, Kueiming Lun
author_sort Zin, A.A.M
collection ePrints
description In this paper, a few approaches to detect, localize, and investigate the feasibility of classifying various types of power quality disturbances are presented. The approaches are based on wavelet transform analysis, particularly the Paul, Gaussian, and Daubechies wavelet transform. The key idea underlying the approaches are to decompose a given disturbance signal into other signals which represents transforming a one-dimensional time series into two-dimensional time-frequency space. The decomposition is performed using the Paul, Gaussian, and Daubechies wavelet transform techniques. The techniques to detect and localize disturbances with actual power line disturbances are proposed, and then demonstrated and tested. In order to enhance the detection outcomes the squared wavelet transform coefficients of the analyzed power line signal are utilized. Based on the results of the detection and localization, an initial investigation of the ability to uniquely characterize various types of power quality disturbances is carried out. This investigation is based on characterizing the uniqueness of the squared wavelet transform coefficients for each power quality disturbance.
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spelling utm.eprints-75252017-10-23T03:53:52Z http://eprints.utm.my/7525/ Power quality disturbance magnitude characterization using wavelet transformation analysis part 1-theory Zin, A.A.M Goh, H.H Lo, Kueiming Lun TK Electrical engineering. Electronics Nuclear engineering In this paper, a few approaches to detect, localize, and investigate the feasibility of classifying various types of power quality disturbances are presented. The approaches are based on wavelet transform analysis, particularly the Paul, Gaussian, and Daubechies wavelet transform. The key idea underlying the approaches are to decompose a given disturbance signal into other signals which represents transforming a one-dimensional time series into two-dimensional time-frequency space. The decomposition is performed using the Paul, Gaussian, and Daubechies wavelet transform techniques. The techniques to detect and localize disturbances with actual power line disturbances are proposed, and then demonstrated and tested. In order to enhance the detection outcomes the squared wavelet transform coefficients of the analyzed power line signal are utilized. Based on the results of the detection and localization, an initial investigation of the ability to uniquely characterize various types of power quality disturbances is carried out. This investigation is based on characterizing the uniqueness of the squared wavelet transform coefficients for each power quality disturbance. Elsevier Ltd. 2008 Article PeerReviewed Zin, A.A.M and Goh, H.H and Lo, Kueiming Lun (2008) Power quality disturbance magnitude characterization using wavelet transformation analysis part 1-theory. International Journal of Power and Energy Systems, 28 (2). pp. 186-189.
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Zin, A.A.M
Goh, H.H
Lo, Kueiming Lun
Power quality disturbance magnitude characterization using wavelet transformation analysis part 1-theory
title Power quality disturbance magnitude characterization using wavelet transformation analysis part 1-theory
title_full Power quality disturbance magnitude characterization using wavelet transformation analysis part 1-theory
title_fullStr Power quality disturbance magnitude characterization using wavelet transformation analysis part 1-theory
title_full_unstemmed Power quality disturbance magnitude characterization using wavelet transformation analysis part 1-theory
title_short Power quality disturbance magnitude characterization using wavelet transformation analysis part 1-theory
title_sort power quality disturbance magnitude characterization using wavelet transformation analysis part 1 theory
topic TK Electrical engineering. Electronics Nuclear engineering
work_keys_str_mv AT zinaam powerqualitydisturbancemagnitudecharacterizationusingwavelettransformationanalysispart1theory
AT gohhh powerqualitydisturbancemagnitudecharacterizationusingwavelettransformationanalysispart1theory
AT lokueiminglun powerqualitydisturbancemagnitudecharacterizationusingwavelettransformationanalysispart1theory