魏海东,徐世媚,黄耀英,等. 大坝安全巡检无人机最优图像采集工况试验研究[J]. 水利水运工程学报.. doi: 10.12170/20230412001
引用本文: 魏海东,徐世媚,黄耀英,等. 大坝安全巡检无人机最优图像采集工况试验研究[J]. 水利水运工程学报.. doi: 10.12170/20230412001
(WEI Haidong, XU Shimei, HUANG Yaoying, et al. Experimental investigation of the optimal image acquisition conditions for Unmanned Aerial Vehicles (UAVs) used in dam safety inspections[J]. Hydro-Science and Engineering(in Chinese)). doi: 10.12170/20230412001
Citation: (WEI Haidong, XU Shimei, HUANG Yaoying, et al. Experimental investigation of the optimal image acquisition conditions for Unmanned Aerial Vehicles (UAVs) used in dam safety inspections[J]. Hydro-Science and Engineering(in Chinese)). doi: 10.12170/20230412001

大坝安全巡检无人机最优图像采集工况试验研究

Experimental investigation of the optimal image acquisition conditions for Unmanned Aerial Vehicles (UAVs) used in dam safety inspections

  • 摘要: 为提高大坝安全巡检无人机图像采集的有效性,针对拍摄距离、风速和光照条件三项重要影响因素,基于大疆Phantom 4 Pro无人机开展试验,分别结合图像自适应阈值二值化、无人机位移及深度学习方法对图像的信息提取效果进行评估,从而研究无人机大坝巡检最优的图形采集工况。研究结果表明,在拍摄距离为3 m、单向风速为2.5~4.0 m/s范围内、晴天背阳的光照条件下,无人机悬停能力较好,不会与被拍摄物体表面发生碰撞,且采集的图像质量最佳。优化了无人机图像采集方案,为基于无人机巡视大坝工作提供参考依据。未来可以进一步应用自动化巡检系统、传感器技术和智能飞行控制算法,实现无人机在大坝安全巡检中的全面应用。

     

    Abstract: In order to enhance the effectiveness of Unmanned Aerial Vehicle (UAV) image acquisition for dam safety inspections, this study focuses on three crucial factors: shooting distance, wind speed, and illumination conditions. Using the DJI Phantom 4 Pro UAV as the experimental platform, a series of UAV experiments were conducted under varying shooting distances, wind speeds, and illumination conditions. The image information extraction effectiveness was evaluated through a combination of image adaptive binarization, UAV displacement analysis, and deep learning techniques. The objective was to determine the optimal conditions for acquiring high-quality images during UAV-based dam inspections. The results indicate that the UAV demonstrates excellent hovering capabilities and avoids collision with the target surface under specific conditions, including a shooting distance of 3 meters, a unidirectional wind speed ranging from 2.5 to 4.0 m/s, and favorable sunny backlit conditions. This study optimizes the image acquisition scheme for UAV inspections and provides valuable insights for dam safety inspections utilizing UAV technology. Furthermore, future advancements in automatic inspection systems, sensor technology, and intelligent flight control algorithms can further enhance the comprehensive application of UAVs in dam safety inspections.

     

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