Finding an automated fault identification method for transmission lines has always been a hot research issue in the field of power applications. With the rapid development of automated data acquisition equipment such as UAV and artificial neural network technology, more and more researchers begin to pay more attention on the issue of Transmission Lines Fault Recognition based on the Line Patrol UAV. In this paper, based on an in-depth literature survey, we provide a representative description and analysis for UAV powerline detection from two aspects. According to the difference of data acquisition strategies (radar images, infrared images, ultraviolet images, visible images), we first discuss the advantages and disadvantages of each data source based on the introducing the representative methods which is designed to deal with these data sources. We also introduce the processing ideas of efficient information processing algorithms of UAV powerline fault detection. Finally, we summary the main challenges in the field of transmission lines fault recognition based on line patrol UAV and prospects its possible future development direction.
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