基于BEVFusion算法的电力巡检无人机研究

Research on power line inspection UAVs based on BEVFusion algorithm

随着电力系统的快速发展和无人机技术的不断进步,电力巡检逐渐从传统的人力巡检向智能化、自动化方向转变。针对这种趋势,提出了一种基于BEVFusion算法的电力巡检无人机优化方案。BEVFusion算法结合了鸟瞰图视角与多传感器融合技术,综合利用毫米波雷达和单目相机的数据,能够提供更为准确和全面的环境感知能力。通过在多种典型电力巡检场景中的试验,验证了该算法在目标检测、路径规划和故障识别等方面的有效性。试验结果表明,基于BEVFusion算法的无人机在电力巡检任务中表现出了较高的效率和准确性,相较于传统方法具有明显优势。该研究不仅为电力巡检提供了一种新的技术手段,也为无人机在其他复杂环境中的应用提供了重要参考。

With the rapid development of power systems and the continuous advancement of drone technology,power line inspection is gradually transitioning from traditional manual methods to intelligent and automated approaches.In response to this trend,we propose an optimized solution for power line inspection drones based on the BEVFusion algorithm.The BEVFusion algorithm combines bird’s-eye view perspectives with multi-sensor fusion technology,utilizing data from millimeter-wave radar and monocular cameras to provide more accurate and comprehensive environmental perception capabilities.Experiments conducted in various typical power inspection scenarios have validated the effectiveness of this algorithm in target detection,path planning,and fault identification.The results indicate that drones equipped with the BEVFusion algorithm demonstrate higher efficiency and accuracy in power line inspection tasks,showing significant advantages over traditional methods.This study not only offers a new technical approach for power line inspection but also provides valuable references for the application of drones in other complex environments.