Abdelaziz LAKEHAL and Zine ghemari (2014) Fault diagnosis of electrical power transformer based on water content analysis using Bayesian network. IEEE, Electrical Sciences and Technologies in Maghreb (CISTEM), 2014 International Conference on , Tunis, Tunisia, November 03-06, 2014
Scientific Publications
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Abstract
Water content and breakdown voltage of dielectric oil are generally unstable parameters. Exceeding limit permissible threshold of one of parameters implies corrective actions because they are directly related to the oil ability to isolate. In this paper a model based on a Bayesian network (BN) is used to diagnose the causes of transformer failures. The proposed model is used to diagnose the water content in the oil, and to predict the breakdown voltage. A case study of a main transformer (MT) of a power plant is presented to show the effectiveness of our model.
Information
| Item Type | Conference |
|---|---|
| Divisions |
» Faculty of Science and Technology |
| ePrint ID | 332 |
| Date Deposited | 2015-04-08 |
| Further Information | Google Scholar |
| URI | https://univ-soukahras.dz/en/publication/article/332 |
BibTex
@inproceedings{uniusa332,
title={Fault diagnosis of electrical power transformer based on water content analysis using Bayesian network},
author={Abdelaziz LAKEHAL and Zine ghemari},
year={2014},
booktitle={IEEE, Electrical Sciences and Technologies in Maghreb (CISTEM), 2014 International Conference on}
}
title={Fault diagnosis of electrical power transformer based on water content analysis using Bayesian network},
author={Abdelaziz LAKEHAL and Zine ghemari},
year={2014},
booktitle={IEEE, Electrical Sciences and Technologies in Maghreb (CISTEM), 2014 International Conference on}
}