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Application of Physical-Chemical Data in Estimation of Dissolved Gases in Insulating Mineral Oil for Power Transformer Incipient Fault Diagnosis with ANN

by Hasmat Malik, Tarkeshwar, Mantosh Kr, Amit Kr Yadav, B.anil Kr
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 21
Year of Publication: 2012
Authors: Hasmat Malik, Tarkeshwar, Mantosh Kr, Amit Kr Yadav, B.anil Kr
10.5120/5842-8057

Hasmat Malik, Tarkeshwar, Mantosh Kr, Amit Kr Yadav, B.anil Kr . Application of Physical-Chemical Data in Estimation of Dissolved Gases in Insulating Mineral Oil for Power Transformer Incipient Fault Diagnosis with ANN. International Journal of Computer Applications. 41, 21 ( March 2012), 43-50. DOI=10.5120/5842-8057

@article{ 10.5120/5842-8057,
author = { Hasmat Malik, Tarkeshwar, Mantosh Kr, Amit Kr Yadav, B.anil Kr },
title = { Application of Physical-Chemical Data in Estimation of Dissolved Gases in Insulating Mineral Oil for Power Transformer Incipient Fault Diagnosis with ANN },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 21 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 43-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number21/5842-8057/ },
doi = { 10.5120/5842-8057 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:30:14.705104+05:30
%A Hasmat Malik
%A Tarkeshwar
%A Mantosh Kr
%A Amit Kr Yadav
%A B.anil Kr
%T Application of Physical-Chemical Data in Estimation of Dissolved Gases in Insulating Mineral Oil for Power Transformer Incipient Fault Diagnosis with ANN
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 21
%P 43-50
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, Artificial Neural Networks are used to solve a complex problem concerning to power transformers and characterized by non-linearity and hard dynamic modeling. The operation conditions and integrity of a power transformer can be detected by analysis of physical-chemical and chromatographic isolating oil, allowing establish procedures for operating and maintaining the equipment. However, while the costs of physical-chemical tests are smaller, the chromatographic analysis is more informative. This work presents an estimation study of the information that would be obtained in the chromatographic test from the physical-chemical analysis through Artificial Neural Networks. Thus, the power utilities can achieve greater reliability in the prediction of incipient failures at a lower cost. The results show this strategy to be a promising, with accuracy of 100% in best cases. The authors have estimated the dissolved gases in insulating mineral oil using proposed method for 185 transformers. As a result, appropriate maintenance scenario can be planned.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Aging Artificial Neural Network (ann) Incipient Fault Uv/vis Transformer Diagnosis

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