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://www.univ-soukahras.dz/en/publication/article/332

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