Subtle Classification and Identification Method of Surface Discharge Intensity of Insulators Based on Arc Area

FANG Chunhua; PAN Minglong; HUANG Li; ZHOU Yuqiu; ZHANG Shuai; LI Jing

doi:10.13296/j.1001-1609.hva.2019.02.018

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Subtle Classification and Identification Method of Surface Discharge Intensity of Insulators Based on Arc Area

更新时间：2025-04-26

- Subtle Classification and Identification Method of Surface Discharge Intensity of Insulators Based on Arc Area
- High VoltageApparatus Vol. 55, Issue 2, Pages: 126-132+139(2019)
- 作者机构：
  
  1. 三峡大学电气与新能源学院
  2. 广东电网有限责任公司清远供电局
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2019.02.018
  CLC： TM216
- Published：2019
- 稿件说明：
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[1]方春华,潘明龙,黄立,周雨秋,张帅,李景.基于电弧面积绝缘子表面放电强度精细分类与识别方法[J].高压电器,2019,55(02):126-132+139.

FANG Chunhua, PAN Minglong, HUANG Li, et al. Subtle Classification and Identification Method of Surface Discharge Intensity of Insulators Based on Arc Area[J]. High voltageapparatus, 2019, 55(2): 126-132+139.
[1]方春华,潘明龙,黄立,周雨秋,张帅,李景.基于电弧面积绝缘子表面放电强度精细分类与识别方法[J].高压电器,2019,55(02):126-132+139. DOI： 10.13296/j.1001-1609.hva.2019.02.018.

FANG Chunhua, PAN Minglong, HUANG Li, et al. Subtle Classification and Identification Method of Surface Discharge Intensity of Insulators Based on Arc Area[J]. High voltageapparatus, 2019, 55(2): 126-132+139. DOI： 10.13296/j.1001-1609.hva.2019.02.018.

摘要

由于绝缘子放电的复杂性和随机性

目前研究只将其定性的划分为微弱放电、中等强度放电和强放电

然后利用泄漏电流对其进行分类识别来实现绝缘子运行状态的判定和预警。文中运用图像处理技术将绝缘子放电试验所得图片中的电弧面积提取出来

以此量化放电强度

然后依据电弧面积将中等强度放电又细分为级别一、级别二和级别三

并分别在3个强度等级下提取了3组泄漏电流样本

运用数理统计、小波变换等方法对泄漏电流波形提取了17个特征量

并采用了主成分法和支持向量机对泄漏电流按照强度级别进行分类识别

测试结果准确率达到93%以上。研究结果表明:利用该方法能准确的对绝缘子中等强度放电进行进一步细化

并能按强度级别对泄漏电流进行分类识别

为判断绝缘子运行状态和评估其放电危害性提供更精确的依据。

Abstract

The current study only divides qualitatively the discharge intensity of the insulator into weak discharge

moderate intensity discharge and strong discharge due to its complexity and randomness

then leakage current is classified in accordance with the discharge intensity to identify the status of the insulator.In this paper the area of discharge arc is extracted by the image processing techniques in the image which obtained from insulator discharge test

then

the intensity of discharge is quantified.Based on this the moderate discharge is subdivided into level 1

level 2 and level 3 according to the discharge arc area

and 3 groups of samples of leakage current are taken under the three intensity level respectively.17 features of leakage current waveform are extracted by using the method of mathematical statistics and wavelet transform

and then the principal component analysis and support vector machine are used to classify and recognize leakage current according to intensity level

the accuracy rate of test results is more than93%.The research results show that the method can be used to further refine the moderate intensity discharge of insulators and classify the leakage current according to the intensity level.It provides a more accurate basis for judging the operation state of insulators and evaluating the discharge harmfulness.

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