Scientific Publications

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Abstract

Electrical power transformer is critical equipment in power plant and electrical power transmission and distribution. To facilitate the fault diagnosis of this electrical transformer a Bayesian network was developed and used for information fusion. 7 transformer elements were examined. 22 faults were taken care of in this study. 14 information’s mainly taken from existing test and measurement equipment have been used and the main lines of their interpretations have been formulated. The main result of this contribution was a useful fault diagnosis manual for handling real problems in electrical power transformer maintenance. This contribution can help and serve as an expert decision support system for maintenance engineer. By detecting, diagnosing and decision making, the availability of electrical power transformer was improved.


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