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Partial Discharge Pattern Recognition of XLPE Cable Connector Based on Support Vector Machine

机译:基于支持向量机的XLPE电缆连接器的局部放电模式识别

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According to the characteristics of partial discharge of XLPE cable connector, a method based on support vector machine for Pattern Recognition is proposed in this paper. Six statistical operators, which include skewness, steepness, discharge factor, phase asymmetry, cross-correlation coefficient, and the modified cross-correlation coefficient, are considered as characteristic quantities. This paper describes a threedimensional map structure of partial discharge, elaborates the extraction process of characteristic quantities, and analyses the basic principles based on support vector machines in detail. Finally, four kinds of typical partial discharge models are simulated in laboratory, and the experimental results show that the method is feasible and has significant effect.
机译:根据XLPE电缆连接器的局部放电的特性,本文提出了一种基于支持向量机的方法,用于图案识别。六个统计算子包括偏斜,陡度,排放因子,相位不对称性,互相关系数和改进的互相关系数,被认为是特征量。本文介绍了局部放电的三维地图结构,详细分析了基于支持向量机的基本原理。最后,在实验室中模拟了四种典型的局部放电模型,实验结果表明该方法是可行的并且具有显着效果。

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