Fault Diagnosis of Oil-filled Power Transformer using DGA and Intelligent Probability Model
نویسندگان
چکیده
منابع مشابه
DGA Interpretation of Oil Filled Transformer Condition Diagnosis
Copyright 2012 KIEEME. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited. pISSN: 1229-7607 eISSN: 2092-7592 DOI: http://dx...
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Faults and damage in oil-filled power transformers has a devastating effect on the overall reliability of electrical power systems. Several factors, especially electrical and thermal stresses age the transformer and subject them to incipient faults. These faults, if left undetected will cause deterioration and eventually lead to failure of the transformer [1]. The presence of faults such as arc...
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Missing values are prevalent in real-world datasets and they may reduce predictive performance of a learning algorithm. Dissolved Gas Analysis (DGA), one of the most deployable methods for detecting and predicting incipient faults in power transformers is one of the casualties. Thus, this paper proposes filling-in the missing values found in a DGA dataset using the k-nearest neighbor imputation...
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Dissolved Gas Analysis (DGA) is one of the most common techniques to detect the incipient faults in the oil-filled power transformers. In this paper, a new approach of DGA technique is proposed to overcome the conflict that takes place in the traditional interpretation techniques for transformer fault diagnosis. The new approach is based on the analysis of 386 dissolved gas samples data set tha...
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ژورنال
عنوان ژورنال: The Transactions of the Korean Institute of Electrical Engineers P
سال: 2016
ISSN: 1229-800X
DOI: 10.5370/kieep.2016.65.3.188