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.