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交联聚乙烯电缆局部放电灰度图像的模式识别
引用本文:廖瑞金,犹登亮,周湶,刘玲.交联聚乙烯电缆局部放电灰度图像的模式识别[J].高压电器,2007,43(2):85-87,91.
作者姓名:廖瑞金  犹登亮  周湶  刘玲
作者单位:重庆大学高电压与电工新技术教育部重点实验室,重庆,400044
摘    要:局部放电模式识别是判断电气设备绝缘状况的重要方法之一。分形理论在局部放电特征的提取上是一种行之有效的方法,通过构造交联聚乙烯(XLPE)电缆局部放电信号的灰度图像,采用逐段搜索确定无标度区域,并采用盒维数与信息维数为特征量作为人工神经网络的输入,对局部放电缺陷进行模式识别。研究表明分形特征在局部放电模式识别上具有良好的效果。

关 键 词:局部放电  分形理论  无标度区  人工神经网络  模式识别
文章编号:1001-1609(2007)02-0085-03
修稿时间:2006-08-25

Pattern Recognition of XLPE Cable Partial Discharge Base on Gray Image
LIAO Rui-jin,YOU Deng-liang,ZHOU Quan,LIU Ling.Pattern Recognition of XLPE Cable Partial Discharge Base on Gray Image[J].High Voltage Apparatus,2007,43(2):85-87,91.
Authors:LIAO Rui-jin  YOU Deng-liang  ZHOU Quan  LIU Ling
Affiliation:The key Laboratory of High Voltage Engineering and Electrical New Technology, Ministry of Education, Chongqing University, Chongqing 400044, China
Abstract:Partial discharge pattern recognition is an important way to assess insulation condition of electrical equipment.Fractal theory is effective to extract features of PD.Based on the construction of gray image of XLPE PD signals,this paper determines the scaleless range by piecewise search,selects the box-dimension and information dimension as the input variables for artificial neural network and carries out PD pattern recognition.Results indicate the extracted fractal characteristics can meet the requirements of PD pattern recognition.
Keywords:partial discharge(PD)  fractal theroy  fractal scaleless range  artificial neural networks  pattern recognition
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