Research of Pattern Recognition of Partial Discharge in Power Transformer Based on Information Fusion
Information fusion theory is an efficient method in partial discharge pattern recognition in recent years. As one of the most important equipments in the power system, partial discharge (PD) affects the transformer's properties in a long-term period. In order to better understand the development of transformer partial discharge, 3 kinds of experimental models simulating discharges were designed and model experiments were performed, meanwhile, the oil-gas data and partial discharge signal were collected to analyze the variable law of the dissolved gases in oil during the development process of the partial discharge. Then, extracting the two-dimensional operator and constructing the BP/RBF neural network to primary recognize discharge type of partial discharge in transformer. Based on this, fusion the output of neural network and oil gas features to give the last results of pattern recognition. The finally experiments show that: information fusion have enough ability to recognize different types of partial discharge.
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Document Type: Research Article
Publication date: 2012-03-01
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