An Comprehensive Detection Method for Fault Location and Fire Risk Judgment of Substation Power Equipment

Hao Yu, Jian Zhang, Junzhou Li, Yanbo Liu
{"title":"An Comprehensive Detection Method for Fault Location and Fire Risk Judgment of Substation Power Equipment","authors":"Hao Yu, Jian Zhang, Junzhou Li, Yanbo Liu","doi":"10.1109/AUTEEE52864.2021.9668720","DOIUrl":null,"url":null,"abstract":"In view of the lack of fault identification and fire risk prediction of power equipment detection in substation, an comprehensive detection method for fault location and fire risk judgment is proposed in this paper. The maximum information entropy theory is used to deal with the fuzziness of infrared image to improve the imaging contrast. The Gaussian mixture modeling and temporary background updating are used to locate suspicious faults. The temperature and area of remote and small target are identified by subpixel irradiance analysis. The temperature rise and fire risk characteristics are constructed and the equipment defect and fire risk levels are defined, which is to realize the advance warning of equipment abnormality and fire risk. This method is applied in the equipment inspection of a 500kV substation to verify the effectiveness and practicability of the method.","PeriodicalId":406050,"journal":{"name":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"1598 1-2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AUTEEE52864.2021.9668720","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In view of the lack of fault identification and fire risk prediction of power equipment detection in substation, an comprehensive detection method for fault location and fire risk judgment is proposed in this paper. The maximum information entropy theory is used to deal with the fuzziness of infrared image to improve the imaging contrast. The Gaussian mixture modeling and temporary background updating are used to locate suspicious faults. The temperature and area of remote and small target are identified by subpixel irradiance analysis. The temperature rise and fire risk characteristics are constructed and the equipment defect and fire risk levels are defined, which is to realize the advance warning of equipment abnormality and fire risk. This method is applied in the equipment inspection of a 500kV substation to verify the effectiveness and practicability of the method.
变电站电力设备故障定位与火灾风险判断的综合检测方法
针对变电站电力设备检测在故障识别和火灾风险预测方面的不足,提出了一种用于故障定位和火灾风险判断的综合检测方法。利用最大信息熵理论处理红外图像的模糊性,提高成像对比度。利用高斯混合建模和临时背景更新对可疑故障进行定位。采用亚像元辐照度分析方法对远、小目标的温度和面积进行识别。构建温升和火灾危险特征,定义设备缺陷和火灾危险等级,实现设备异常和火灾危险预警。将该方法应用于某500kV变电站的设备检测,验证了该方法的有效性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信