Pattern Recognition Method of UHF PD Envelope Signal in GIS Based on Rough Set Reduction

LI Qing1; DUAN Da-peng2; QIU Wu-bin1; CAI Kai-sui1; SHENG Ge-hao3; HUANG Xing-quan1; JIANG Xiu-chen3

doi:10.13296/j.1001-1609.hva.2012.03.003

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Pattern Recognition Method of UHF PD Envelope Signal in GIS Based on Rough Set Reduction

更新时间：2025-04-26

- Pattern Recognition Method of UHF PD Envelope Signal in GIS Based on Rough Set Reduction
- High VoltageApparatus Vol. 48, Issue 3, Pages: 6-11(2012)
- 作者机构：
  
  1. 河南电力试验研究院
  2. 北京电力科学研究院
  3. 上海交通大学电子信息与电气工程学院
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2012.03.003
  CLC： TM595;TM855
- Published：2012
- 稿件说明：
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[1]李清,段大鹏,邱武斌,蔡开穗,盛戈皞,黄兴泉,江秀臣.基于粗糙集降维理论的GIS超高频局放包络模式识别方法[J].高压电器,2012,48(03):6-11.

LI Qing1, DUAN Da-peng2, QIU Wu-bin1, et al. Pattern Recognition Method of UHF PD Envelope Signal in GIS Based on Rough Set Reduction[J]. High voltageapparatus, 2012, 48(3): 6-11.
[1]李清,段大鹏,邱武斌,蔡开穗,盛戈皞,黄兴泉,江秀臣.基于粗糙集降维理论的GIS超高频局放包络模式识别方法[J].高压电器,2012,48(03):6-11. DOI： 10.13296/j.1001-1609.hva.2012.03.003.

LI Qing1, DUAN Da-peng2, QIU Wu-bin1, et al. Pattern Recognition Method of UHF PD Envelope Signal in GIS Based on Rough Set Reduction[J]. High voltageapparatus, 2012, 48(3): 6-11. DOI： 10.13296/j.1001-1609.hva.2012.03.003.

摘要

判断局部放电类型与局放包络信号之间的关系是实现评估气体绝缘金属封闭开关设备（GIS）的绝缘状态以及制定合理的维修策略的重要前提。笔者利用粗糙集降维理论

先对表征UHF PD包络信号的37个特征向量所组成的特征矩阵进行了离散化与差别矩阵约简

然后利用简约后的特征向量结合BP神经网络分类器

对4种不同类型的UHF PD包络信号进行了模式识别

结果表明此方法具有较高的识别率。

Abstract

Determining the relationship between partial discharge（PD） type and PD envelope signal is an important premise to assess the insulation state of gas-insulated metal-enclosed switchgear（GIS） and to make rational maintenance strategy.The matrix of 37 feature vectors

with which a UHF PD envelope signal is characterized

is discretized

and its difference matrix is reduced with the dimension reduction rough set theory.Then the reduced feature vectors combining with the BP neural network classifier are applied to pattern recognition of four different types of UHF PD envelope signals.The results show a high recognition rate of the proposed method.

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