中图分类号：TP391.41 文献标志码：A DOI: 10.16157/j.issn.0258-7998.233863
中文引用格式：薛倩楠，王剑，刘涛，等. 一种基于深度学习模型的无人机巡检输电线路山火检测方法[J]. 电子技术应用，2023，49(10)：46-52.
英文引用格式：Xue Qiannan，Wang Jian，Liu Tao，et al. A mountain fire detecting method based on the deep learning model for UAV-based transmission line patrol inspection[J]. Application of Electronic Technique，2023，49(10)：46-52.
A mountain fire detecting method based on the deep learning model for UAV-based transmission line patrol inspection
Xue Qiannan1，Wang Jian1，Liu Tao2，Yan Xiying2
(1.State Grid Shaanxi Electric Power Company Xi'an Power Supply Company， Xi'an 710032， China； 2.Xi'an İnnovision Technology Co.， Limited， Xi'an 710075， China)
Abstract：The background of the power transmission line inspection image is complex, and the target detection is easy to be disturbed. Based on YOLOX neural network model, this paper proposes a method of power transmission line mountain fire detection. Firstly, the backbone feature extraction network framework of YOLOX is adopted, and the conventional convolution of the multi-scale feature extraction module is replaced by deformable convolution. Secondly, the fusion of channel attention and spatial attention modules is added in the enhanced feature extraction stage, which can adapt to the variable shape of flames, extract mountain fire features more effectively, and thus improve the accuracy of target detection. The experiment verifies the effectiveness of the proposed method.
Key words :power transmission line inspection；mountain fire identification；neural network；target detection；YOLOX
