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Field Applications of Ultra High Frequency Techniques for Defect Detection in GIS

The reliable and stable operation of power apparatus is important for the development of GIS. It is important to utilize condition monitoring technologies and anticipate possible failures in advance. Many papers have been published about the partial discharge detection with UHF or X-ray in laborator...

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Autores principales: Xiong, Jun, Wang, Yuan, Ma, Guo-Ming, Zhang, Qiang, Zheng, Shu-Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111932/
https://www.ncbi.nlm.nih.gov/pubmed/30049935
http://dx.doi.org/10.3390/s18082425
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author Xiong, Jun
Wang, Yuan
Ma, Guo-Ming
Zhang, Qiang
Zheng, Shu-Sheng
author_facet Xiong, Jun
Wang, Yuan
Ma, Guo-Ming
Zhang, Qiang
Zheng, Shu-Sheng
author_sort Xiong, Jun
collection PubMed
description The reliable and stable operation of power apparatus is important for the development of GIS. It is important to utilize condition monitoring technologies and anticipate possible failures in advance. Many papers have been published about the partial discharge detection with UHF or X-ray in laboratory, but seldom in field application. Thus, many engineers at project sites are not familiar with the current professional diagnosis techniques. Recently, during the GIS routine data analysis obtained by partial discharge online monitoring system, it was found that the UHF monitoring signals’ developing trend of the 220 kV GIS No. 2 high-voltage side of transformer in phase C at an actual station was abnormal and needed further detection. In order to precisely investigate the problem and then guide the operation and maintenance activities, a series of professional diagnoses were conducted. Three new types of partial discharge detection and positioning methods were applied for accuracy, including UHF partial discharge detection based on multi-stage amplified signal demodulation and multiple weighted averages processing; the partial discharge detection based on the signal radiation hole of insulation disk at the ground connection; and the positioning method based on UHF-SHF. After a series of troubleshooting works, the partial discharge defects have been diagnosed, and the case can be referred in the field monitoring of GIS.
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spelling pubmed-61119322018-08-30 Field Applications of Ultra High Frequency Techniques for Defect Detection in GIS Xiong, Jun Wang, Yuan Ma, Guo-Ming Zhang, Qiang Zheng, Shu-Sheng Sensors (Basel) Article The reliable and stable operation of power apparatus is important for the development of GIS. It is important to utilize condition monitoring technologies and anticipate possible failures in advance. Many papers have been published about the partial discharge detection with UHF or X-ray in laboratory, but seldom in field application. Thus, many engineers at project sites are not familiar with the current professional diagnosis techniques. Recently, during the GIS routine data analysis obtained by partial discharge online monitoring system, it was found that the UHF monitoring signals’ developing trend of the 220 kV GIS No. 2 high-voltage side of transformer in phase C at an actual station was abnormal and needed further detection. In order to precisely investigate the problem and then guide the operation and maintenance activities, a series of professional diagnoses were conducted. Three new types of partial discharge detection and positioning methods were applied for accuracy, including UHF partial discharge detection based on multi-stage amplified signal demodulation and multiple weighted averages processing; the partial discharge detection based on the signal radiation hole of insulation disk at the ground connection; and the positioning method based on UHF-SHF. After a series of troubleshooting works, the partial discharge defects have been diagnosed, and the case can be referred in the field monitoring of GIS. MDPI 2018-07-26 /pmc/articles/PMC6111932/ /pubmed/30049935 http://dx.doi.org/10.3390/s18082425 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xiong, Jun
Wang, Yuan
Ma, Guo-Ming
Zhang, Qiang
Zheng, Shu-Sheng
Field Applications of Ultra High Frequency Techniques for Defect Detection in GIS
title Field Applications of Ultra High Frequency Techniques for Defect Detection in GIS
title_full Field Applications of Ultra High Frequency Techniques for Defect Detection in GIS
title_fullStr Field Applications of Ultra High Frequency Techniques for Defect Detection in GIS
title_full_unstemmed Field Applications of Ultra High Frequency Techniques for Defect Detection in GIS
title_short Field Applications of Ultra High Frequency Techniques for Defect Detection in GIS
title_sort field applications of ultra high frequency techniques for defect detection in gis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111932/
https://www.ncbi.nlm.nih.gov/pubmed/30049935
http://dx.doi.org/10.3390/s18082425
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