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This paper presents a multi-source data and information fusion framework for power transformer condition assessment. The proposed method adopts Bayesian Network (BN), which can integrate every piece of data and information obtained from different transformer diagnostic measurements. Within the Bayesian Network, Monte Carlo and Bootstrap methods are employed to extract the most informative characteristics...
Transformer oil tests have been conducted in utility companies as one of the major tools for evaluating the integrity of transformer insulation. However, the information obtained from different types of oil tests (the result of a particular type of oil test is termed as an oil characteristic in this paper) may have different significant degree in revealing the condition of a transformer's insulation...
This work investigates the practical application of support vector machine (SVM) to power transformer condition assessment. Partiuclarly, this paper proposes to integrate the SVM algorithm with two heuristic optimization algorithms which are particle swarm optimization algorithm (PSO) and genetic algorithm optimization (GA). These two optimization algorithms are used for efficiently and effectively...
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