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by Zhi-hua Zhou, Yuan Jiang, Xu-ri Yin, Shi-fu Chen
http://cs.nju.edu.cn/people/zhouzh/zhouzh.files/publication/iea-aie02.pdf
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Abstract:
Abstract. In this paper, visualization and neural network techniques are applied together to a power transformer condition monitoring system. Through visualizing the data from the chromatogram of oil-dissolved gases by 2-D and/or 3-D graphs, the potential failures of the power transformers become easy to be identified. Through employing some specific neural network techniques, the data from the chromatogram of oil-dissolved gases as well as those from the electrical inspections can be effectively analyzed. Experiments show that the described system works quite well in condition monitoring of power transformers. 1.
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