Chao Su, Xiaomei Wu, Yanming Guo, Chun Sing Lai, Liang Xu, Xuan Zhao
{"title":"Automatic Multi-source Data Fusion Technique of Powerline Corridor using UAV Lidar","authors":"Chao Su, Xiaomei Wu, Yanming Guo, Chun Sing Lai, Liang Xu, Xuan Zhao","doi":"10.1109/ISC255366.2022.9922293","DOIUrl":null,"url":null,"abstract":"With the increasing scale and complexity of powerline construction, the challenges of powerline system operation and maintenance are gradually increasing. The research and application of unmanned aerial vehicle (UAV) Lidar technology for powerline inspections is developing rapidly. The Lidar point cloud and visible light measurement are processed intelligently by the powerline multi-source and heterogeneous data automatic fusion technology. Then the three-dimensional model of the powerline system and electrical equipment is obtained. Consequently, the efficient resolving of point cloud data for powerlines, identification of equipment locations and types are realized. The fast measurement and elaborating modeling of the three-dimensional system for powerlines is obtained, which may effectively and comprehensively show the operation status of powerlines. The point cloud classification algorithm is adopted in this paper. Experimental results demonstrated that the proposed method performed well in the detection accuracy of identification and classification of lines and pylons in a complex environment. The classification accuracies for transmission lines and distribution lines are 97.26% and 95.29% respectively. The average classification accuracies of both lines and pylons are 80.88% and 82.25%, respectively.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Smart Cities Conference (ISC2)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISC255366.2022.9922293","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
With the increasing scale and complexity of powerline construction, the challenges of powerline system operation and maintenance are gradually increasing. The research and application of unmanned aerial vehicle (UAV) Lidar technology for powerline inspections is developing rapidly. The Lidar point cloud and visible light measurement are processed intelligently by the powerline multi-source and heterogeneous data automatic fusion technology. Then the three-dimensional model of the powerline system and electrical equipment is obtained. Consequently, the efficient resolving of point cloud data for powerlines, identification of equipment locations and types are realized. The fast measurement and elaborating modeling of the three-dimensional system for powerlines is obtained, which may effectively and comprehensively show the operation status of powerlines. The point cloud classification algorithm is adopted in this paper. Experimental results demonstrated that the proposed method performed well in the detection accuracy of identification and classification of lines and pylons in a complex environment. The classification accuracies for transmission lines and distribution lines are 97.26% and 95.29% respectively. The average classification accuracies of both lines and pylons are 80.88% and 82.25%, respectively.