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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Online Access: | http://dx.doi.org/10.1080/23311916.2014.995786 |
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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 |
work_keys_str_mv |
AT vikalringle decisionaboutcriticalityofpowertransformersusingwhitenizationweightfunctionsondgacautionlevels AT vtingole decisionaboutcriticalityofpowertransformersusingwhitenizationweightfunctionsondgacautionlevels |
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