Power Equipment State Recognition Method Based on Binocular Vision Video

Chuanyou Zhang, Zhizhou Sun, Tao Wang, Jian Li, Yafei Wang, G. Shao, Yan Deng, Guoqing Yang
{"title":"Power Equipment State Recognition Method Based on Binocular Vision Video","authors":"Chuanyou Zhang, Zhizhou Sun, Tao Wang, Jian Li, Yafei Wang, G. Shao, Yan Deng, Guoqing Yang","doi":"10.1109/ICDSBA51020.2020.00079","DOIUrl":null,"url":null,"abstract":"A state detection method of power equipment based on Binocular vision video is proposed. The power equipment video stream is obtained by binocular camera, and the inspection image is obtained by extracting the video key frames. The disparity map of the region of interest in the inspection image is calculated, and the distance information distribution is obtained from the disparity map. According to the distance information distribution, the status of electrical equipment is determined. Through the principle of binocular vision ranging, equipment status identification is realized, which provides a new method for the identification of substation equipment status, and realizes the rapid and accurate identification of power equipment status.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSBA51020.2020.00079","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

A state detection method of power equipment based on Binocular vision video is proposed. The power equipment video stream is obtained by binocular camera, and the inspection image is obtained by extracting the video key frames. The disparity map of the region of interest in the inspection image is calculated, and the distance information distribution is obtained from the disparity map. According to the distance information distribution, the status of electrical equipment is determined. Through the principle of binocular vision ranging, equipment status identification is realized, which provides a new method for the identification of substation equipment status, and realizes the rapid and accurate identification of power equipment status.
基于双目视觉视频的电力设备状态识别方法
提出了一种基于双目视觉视频的电力设备状态检测方法。利用双目摄像机获取电力设备视频流,通过提取视频关键帧获得巡检图像。计算检测图像中感兴趣区域的视差图,并从视差图中得到距离信息分布。根据距离信息分布,确定电气设备的状态。通过双目视觉测距原理,实现了设备状态识别,为变电站设备状态识别提供了一种新的方法,实现了电力设备状态的快速准确识别。
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:481959085
Book学术官方微信