An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment
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Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2020-10-21
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Mcode
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Language
en
Pages
13
1036-1048
1036-1048
Series
ELECTRIC POWER COMPONENTS AND SYSTEMS, Volume 48, issue 9-10
Abstract
Partial discharge (PD) diagnostic is an effective tool for condition monitoring of the high-voltage equipment that provides an updated status of the dielectric insulation of the components. Reliability of the diagnostics depends on the quality of the PD measurement techniques and the processing of the measured PD data. The online measured data suffer from various inaccuracies caused by external noise from various sources such as power electronic equipment, radio broadband signals and wireless communication, etc. Therefore, extraction of useful data from the on-site measurements is still a challenge. This article presents a discrete wavelet transform (DWT)-based adaptive denoising algorithm and evaluates its performance. Various decisive steps in applying DWT-based denoising on any signal, including selection of mother wavelet, number of levels in multiresolution decomposition and criteria for reconstruction of the denoised signals are taken by the proposed algorithm and vary from one signal to another withouta human intervention. Hence, the proposed technique is adaptive. The proposed solution can enhance the accuracy of the PD diagnostic for HV power components.Description
Keywords
Adaptive denoising, Discrete wavelet transform (DWT), High voltage, Insulation diagnostics, Online monitoring, Signal denoising
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Citation
Hussain , A , Ahmed , Z , Shafiq , M , Zaher , A , Rashid , Z & Lehtonen , M 2020 , ' An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment ' , Electric Power Components and Systems , vol. 48 , no. 9-10 , pp. 1036-1048 . https://doi.org/10.1080/15325008.2020.1825554
