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Modification of Duval triangle for diagnostic transformer fault through a procedure of dissolved gases analysis

Authors: Sobhy S. Desouky; Ahmed E. Kalas; R. A. Abd El-Aal; Abdel Moneim M. Hassan;

Modification of Duval triangle for diagnostic transformer fault through a procedure of dissolved gases analysis

Abstract

Dissolved gas-in-oil analysis (DGA) is a sensitive and reliable technique for the detection of incipient fault condition within oil-immersed transformers. When the mineral oil is subjected to high thermal or/and electrical stresses, it decomposes and, as a result, gases are generated. This paper presents modification of Duval triangle DGA diagnostic graph to numerical method that is easy to use for diagnosing and the possibility to use for a Matlab program. The evaluation is carried out on DGA data obtained from three different groups of transformers. A Matlab program was developed to automate the evaluation of Duval Triangle graph to numerical modification, Also the fault gases can be generated due to oil decomposing effected by transformer over excitation which increasing the transformer exciting current lead to rising the temperature inside transformer core beside the other causes.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Top 10%
Average
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