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Automatic Multi-source Data Fusion Technique of Powerline Corridor using UAV Lidar

Chao Su, Xiaomei Wu, Guo Yanming, Chun Sing Lai, Liang Xu, Xuan Zhao

20222022 IEEE International Smart Cities Conference (ISC2)13 citationsDOIOpen Access PDF

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.

Topics & Concepts

LidarPoint cloudComputer scienceElectric power transmissionIdentification (biology)Remote sensingSensor fusionReal-time computingMulti-sourceCloud computingPoint (geometry)Artificial intelligenceEngineeringElectrical engineeringGeographyStatisticsBotanyOperating systemMathematicsGeometryBiologyRemote Sensing and LiDAR Applications3D Surveying and Cultural HeritageAdvanced Optical Sensing Technologies
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