Online Monitoring Technology of Power Transformer based on Vibration Analysis

This paper presents a method for the study of the influence of stability of a power transformer on the power system based on the vibration principle. Traditionally, the EMD and EEMD algorithms are employed to test the box vibration signal data of the power transformer under three working conditions....

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Autores principales:	Meng Junhong, Singh Maninder, Sharma Manish, Singh Daljeet, Kaur Preet, Kumar Rajeev
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	power transformer online monitoring multiscale permutation entropy empirical mode decomposition Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/72736dee567e44088456bc4d11f97a12
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id	oai:doaj.org-article:72736dee567e44088456bc4d11f97a12
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spelling	oai:doaj.org-article:72736dee567e44088456bc4d11f97a122021-12-05T14:10:51ZOnline Monitoring Technology of Power Transformer based on Vibration Analysis0334-18602191-026X10.1515/jisys-2020-0112https://doaj.org/article/72736dee567e44088456bc4d11f97a122021-04-01T00:00:00Zhttps://doi.org/10.1515/jisys-2020-0112https://doaj.org/toc/0334-1860https://doaj.org/toc/2191-026XThis paper presents a method for the study of the influence of stability of a power transformer on the power system based on the vibration principle. Traditionally, the EMD and EEMD algorithms are employed to test the box vibration signal data of the power transformer under three working conditions. The proposed method utilizes a partial EMD screening along with MPEEMD method for the online monitoring of power transformer. A complete online monitoring system is designed by using the STM32 processor and LabVIEW system. The proposed system is compared with EMD and EEMD algorithms in terms of the number of IMFs obtained by decomposition, maximum correlation coefficient, and mean square error. The inherent mode correlation, when compared with the mean square error of the reconstructed signal, shows that the reconstruction error of MPEEMD algorithm is 4.762×10−15 which is better than the traditional EMD algorithm. It is observed from the results that the proposed method outperforms both EMD and EEMD algorithms.Meng JunhongSingh ManinderSharma ManishSingh DaljeetKaur PreetKumar RajeevDe Gruyterarticlepower transformeronline monitoringmultiscale permutation entropyempirical mode decompositionScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 554-563 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	power transformer online monitoring multiscale permutation entropy empirical mode decomposition Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	power transformer online monitoring multiscale permutation entropy empirical mode decomposition Science Q Electronic computers. Computer science QA75.5-76.95 Meng Junhong Singh Maninder Sharma Manish Singh Daljeet Kaur Preet Kumar Rajeev Online Monitoring Technology of Power Transformer based on Vibration Analysis
description	This paper presents a method for the study of the influence of stability of a power transformer on the power system based on the vibration principle. Traditionally, the EMD and EEMD algorithms are employed to test the box vibration signal data of the power transformer under three working conditions. The proposed method utilizes a partial EMD screening along with MPEEMD method for the online monitoring of power transformer. A complete online monitoring system is designed by using the STM32 processor and LabVIEW system. The proposed system is compared with EMD and EEMD algorithms in terms of the number of IMFs obtained by decomposition, maximum correlation coefficient, and mean square error. The inherent mode correlation, when compared with the mean square error of the reconstructed signal, shows that the reconstruction error of MPEEMD algorithm is 4.762×10−15 which is better than the traditional EMD algorithm. It is observed from the results that the proposed method outperforms both EMD and EEMD algorithms.
format	article
author	Meng Junhong Singh Maninder Sharma Manish Singh Daljeet Kaur Preet Kumar Rajeev
author_facet	Meng Junhong Singh Maninder Sharma Manish Singh Daljeet Kaur Preet Kumar Rajeev
author_sort	Meng Junhong
title	Online Monitoring Technology of Power Transformer based on Vibration Analysis
title_short	Online Monitoring Technology of Power Transformer based on Vibration Analysis
title_full	Online Monitoring Technology of Power Transformer based on Vibration Analysis
title_fullStr	Online Monitoring Technology of Power Transformer based on Vibration Analysis
title_full_unstemmed	Online Monitoring Technology of Power Transformer based on Vibration Analysis
title_sort	online monitoring technology of power transformer based on vibration analysis
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/72736dee567e44088456bc4d11f97a12
work_keys_str_mv	AT mengjunhong onlinemonitoringtechnologyofpowertransformerbasedonvibrationanalysis AT singhmaninder onlinemonitoringtechnologyofpowertransformerbasedonvibrationanalysis AT sharmamanish onlinemonitoringtechnologyofpowertransformerbasedonvibrationanalysis AT singhdaljeet onlinemonitoringtechnologyofpowertransformerbasedonvibrationanalysis AT kaurpreet onlinemonitoringtechnologyofpowertransformerbasedonvibrationanalysis AT kumarrajeev onlinemonitoringtechnologyofpowertransformerbasedonvibrationanalysis
_version_	1718371672374902784

Online Monitoring Technology of Power Transformer based on Vibration Analysis

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