The WFCM Recognition Method of Gas Corona Discharge Based Image Gray Features

WU Zi-jing; ZHENG Dian-chun; ZHANG Zheng-han; ZHANG Xian-zhong

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The WFCM Recognition Method of Gas Corona Discharge Based Image Gray Features

更新时间：2026-07-10

- The WFCM Recognition Method of Gas Corona Discharge Based Image Gray Features
- Vol. 15, Issue 2, Pages: 14-18(2010)
- 作者机构：
  
  1. 齐齐哈尔大学应用技术学院
  2. 哈尔滨理工大学电气与电子工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： O461;TM851
- Published：2010
- 稿件说明：
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WU Zi-jing, ZHENG Dian-chun, ZHANG Zheng-han, et al. The WFCM Recognition Method of Gas Corona Discharge Based Image Gray Features[J]. 2010, 15(2): 14-18.
DOI：

WU Zi-jing, ZHENG Dian-chun, ZHANG Zheng-han, et al. The WFCM Recognition Method of Gas Corona Discharge Based Image Gray Features[J]. 2010, 15(2): 14-18. DOI：

摘要

模拟了以气体为绝缘介质的高压电器的放电现象

根据气隙几何构型差异

构建了极不均匀场、不均匀场及稍不均匀场电极模型

并根据图像的中心矩不随坐标变换而改变的特性

采集了模型电极间隙的气体电晕放电信息

根据其信息的时空分布

计算了放电信息图像的灰度矩

归一化处理后作为气体介质失效诊断的模式辨识特征量.在分析了传统算法中模糊聚类算法的基础上

详细论述了加权模糊c-均值聚类算法

实验结果表明此方法充分利用了放电信息样本点的密度信息量

有效弥补了传统算法中存在的不足

提高了模式辨识算法收敛速度.

Abstract

In this paper

three kinds of models are structured to simulating the GCD(gas corona discharge) phenomena and sampling spatio-temporal information of the GCD signals under different electric field strengths

and the fuzzy C-means(FCM) and the weighted fuzzy C-means(WFCM) clustering algorithm are explicitly represented and compared.Moreover

the grey intensity moment features of GCD signal waveforms are extracted and taken as input vector matrix for realizing the pattern recognition

and then computer numerical ...

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