Decision about criticality of power transformers using whitenization weight functions on DGA caution levels

Power transformers are the most significant as well as the major asset of any power system network. The condition monitoring and assessment is the main concern in transformer management activities. As a first information source, dissolved gases-in-oil analysis (DGA) is universally accepted. The asse...

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Main Authors: Vikal R. Ingle, V.T. Ingole
Format: Article
Language:English
Published: Taylor & Francis Group 2015-12-01
Series:Cogent Engineering
Subjects:
DGA
Online Access:http://dx.doi.org/10.1080/23311916.2014.995786
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spelling doaj-d632152b86a249e0a2a3b15e7c57667e2020-11-24T22:00:45ZengTaylor & Francis GroupCogent Engineering2331-19162015-12-012110.1080/23311916.2014.995786995786Decision about criticality of power transformers using whitenization weight functions on DGA caution levelsVikal R. Ingle0V.T. Ingole1B.D. College of EngineeringProf. Ram Meghe Institute Technology & ResearchPower transformers are the most significant as well as the major asset of any power system network. The condition monitoring and assessment is the main concern in transformer management activities. As a first information source, dissolved gases-in-oil analysis (DGA) is universally accepted. The assessment of dissolved gases is characteristically observed analogous to grey system analysis. Grey system theory is supportive to the cases, when less information about the system is available. The cluster of grey incidences and whitenization weight functions classifies the factors of same type, in order to simplify a complex system. Three caution levels of key gases specified in IEEE standards are utilized in this study, to whiten the weight functions. The whitenization weight function with lower measure is selected for caution level-1. However, whitenization weight functions with middle measure are preferred for level-2 and level-3. Several key gas samples of the equal rating transformers are collected from gas analyzer section and utilized in condition assessment computations. The test samples are verified with variable and equal weight clustering criteria. The criticality judgment of transformer with variable weight clustering successfully identifies the crucial elements amongst samples.http://dx.doi.org/10.1080/23311916.2014.995786DGAkey gas methodgrey incidence analysiswhitenization weight functionsgrey classes
collection DOAJ
language English
format Article
sources DOAJ
author Vikal R. Ingle
V.T. Ingole
spellingShingle Vikal R. Ingle
V.T. Ingole
Decision about criticality of power transformers using whitenization weight functions on DGA caution levels
Cogent Engineering
DGA
key gas method
grey incidence analysis
whitenization weight functions
grey classes
author_facet Vikal R. Ingle
V.T. Ingole
author_sort Vikal R. Ingle
title Decision about criticality of power transformers using whitenization weight functions on DGA caution levels
title_short Decision about criticality of power transformers using whitenization weight functions on DGA caution levels
title_full Decision about criticality of power transformers using whitenization weight functions on DGA caution levels
title_fullStr Decision about criticality of power transformers using whitenization weight functions on DGA caution levels
title_full_unstemmed Decision about criticality of power transformers using whitenization weight functions on DGA caution levels
title_sort decision about criticality of power transformers using whitenization weight functions on dga caution levels
publisher Taylor & Francis Group
series Cogent Engineering
issn 2331-1916
publishDate 2015-12-01
description Power transformers are the most significant as well as the major asset of any power system network. The condition monitoring and assessment is the main concern in transformer management activities. As a first information source, dissolved gases-in-oil analysis (DGA) is universally accepted. The assessment of dissolved gases is characteristically observed analogous to grey system analysis. Grey system theory is supportive to the cases, when less information about the system is available. The cluster of grey incidences and whitenization weight functions classifies the factors of same type, in order to simplify a complex system. Three caution levels of key gases specified in IEEE standards are utilized in this study, to whiten the weight functions. The whitenization weight function with lower measure is selected for caution level-1. However, whitenization weight functions with middle measure are preferred for level-2 and level-3. Several key gas samples of the equal rating transformers are collected from gas analyzer section and utilized in condition assessment computations. The test samples are verified with variable and equal weight clustering criteria. The criticality judgment of transformer with variable weight clustering successfully identifies the crucial elements amongst samples.
topic DGA
key gas method
grey incidence analysis
whitenization weight functions
grey classes
url http://dx.doi.org/10.1080/23311916.2014.995786
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