Noise suppression in PD signal based on Prony time series energy spectrum

Abstract On‐line partial discharge (PD) monitoring is related to the safe and stable operation of power grid. However, the measured signal is inevitably affected by noise. Among a variety of noises, white noise is the most difficult to suppress and ubiquitous. It mainly determines the Cramer–Rao low...

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Autores principales:	Chang Wang, Chunxiao Yu, Qin Shu, Dakun Zhang, Yuhang He
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2022
Materias:	Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/d854bd2b8881493aa7a575575234fe69
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spelling	oai:doaj.org-article:d854bd2b8881493aa7a575575234fe692021-12-01T10:55:36ZNoise suppression in PD signal based on Prony time series energy spectrum1751-88301751-882210.1049/smt2.12076https://doaj.org/article/d854bd2b8881493aa7a575575234fe692022-01-01T00:00:00Zhttps://doi.org/10.1049/smt2.12076https://doaj.org/toc/1751-8822https://doaj.org/toc/1751-8830Abstract On‐line partial discharge (PD) monitoring is related to the safe and stable operation of power grid. However, the measured signal is inevitably affected by noise. Among a variety of noises, white noise is the most difficult to suppress and ubiquitous. It mainly determines the Cramer–Rao lower bound that cannot be crossed by all methods. This article proposes the Prony time‐series energy spectrum method to suppress white noise in a low signal‐to‐noise ratio environment. This method is divided into two parts: First, Prony time series energy spectrum is used to detect whether there is PD signals in the measured signal. Then, based on the least square method, the PD signal is estimated with the Prony model. In data analysis, this method can suppress ‐10dB white noise, while other methods have performed poorly or even failed under the same conditions. In general, this method has excellent anti‐noise performance compared to several other algorithms.Chang WangChunxiao YuQin ShuDakun ZhangYuhang HeWileyarticleElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIET Science, Measurement & Technology, Vol 16, Iss 1, Pp 1-14 (2022)
institution	DOAJ
collection	DOAJ
language	EN
topic	Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Electrical engineering. Electronics. Nuclear engineering TK1-9971 Chang Wang Chunxiao Yu Qin Shu Dakun Zhang Yuhang He Noise suppression in PD signal based on Prony time series energy spectrum
description	Abstract On‐line partial discharge (PD) monitoring is related to the safe and stable operation of power grid. However, the measured signal is inevitably affected by noise. Among a variety of noises, white noise is the most difficult to suppress and ubiquitous. It mainly determines the Cramer–Rao lower bound that cannot be crossed by all methods. This article proposes the Prony time‐series energy spectrum method to suppress white noise in a low signal‐to‐noise ratio environment. This method is divided into two parts: First, Prony time series energy spectrum is used to detect whether there is PD signals in the measured signal. Then, based on the least square method, the PD signal is estimated with the Prony model. In data analysis, this method can suppress ‐10dB white noise, while other methods have performed poorly or even failed under the same conditions. In general, this method has excellent anti‐noise performance compared to several other algorithms.
format	article
author	Chang Wang Chunxiao Yu Qin Shu Dakun Zhang Yuhang He
author_facet	Chang Wang Chunxiao Yu Qin Shu Dakun Zhang Yuhang He
author_sort	Chang Wang
title	Noise suppression in PD signal based on Prony time series energy spectrum
title_short	Noise suppression in PD signal based on Prony time series energy spectrum
title_full	Noise suppression in PD signal based on Prony time series energy spectrum
title_fullStr	Noise suppression in PD signal based on Prony time series energy spectrum
title_full_unstemmed	Noise suppression in PD signal based on Prony time series energy spectrum
title_sort	noise suppression in pd signal based on prony time series energy spectrum
publisher	Wiley
publishDate	2022
url	https://doaj.org/article/d854bd2b8881493aa7a575575234fe69
work_keys_str_mv	AT changwang noisesuppressioninpdsignalbasedonpronytimeseriesenergyspectrum AT chunxiaoyu noisesuppressioninpdsignalbasedonpronytimeseriesenergyspectrum AT qinshu noisesuppressioninpdsignalbasedonpronytimeseriesenergyspectrum AT dakunzhang noisesuppressioninpdsignalbasedonpronytimeseriesenergyspectrum AT yuhanghe noisesuppressioninpdsignalbasedonpronytimeseriesenergyspectrum
_version_	1718405263345582080

Noise suppression in PD signal based on Prony time series energy spectrum

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