Power inspection technology based on UAV airborne AI module
WANG Hao
DING Guobin
YANG Jiahui
Abstract：According to the requirements for instantaneity and accuracy by UAV inspection of transmission line,the application of YOLOv3 target detection algorithm in UAV inspection airborne AI module was deeply studied.Through the YOLOv3 algorithm for both object detection candidate region selection and object recognition,in combination with the multi-scale feature fusion method,the high accuracy and instantaneity optimization of target detection were realized,and the residual block was used to solve the problem of model degradation.The results of transmission line insulator detection show that the average accuracy of YOLOv3 algorithm can reach 90%.Under the same conditions,the average processing speed of YOLOv3 algorithm is 3.2 times that of Faster RCNN algorithm and 1.6 times that of SSD algorithm.
Keywords：UAV inspectiontarget detectionimage recognitionmulti-scale feature fusionresidual blocktransmission lineinstantaneity
Publication Date：2024-01-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 49-53 )