智能规划无人机巡检路径，大幅提升风电设备检查效率与精度。
Dynamic Trajectory Adaptation for Efficient UAV Inspections of Wind Energy Units
- 动态调整飞行轨迹，结合叶片位置与角度优化巡检路径。
- 巡检时间减少78%，路径缩短17%，叶片覆盖率提升6%。
- 适合风电运维、无人机自动化巡检领域研究人员参考。
本研究提出一种自动化方法，用于确定无人机（UAV）对风力发电机组的巡检轨迹。该方法利用无人机光学传感器，高效采集多个风力设施的数据，综合考虑叶片及其他部件的空间位置。流程包括风力发电机组（WEU）组件分割、叶片桨距角确定，以及在保证安全距离和最佳视角的前提下生成最优飞行路径。计算实验结果表明，相比传统方法，该方法可实现巡检时间降低78%，总路径长度减少17%，平均叶片表面覆盖率达6%提升；同时，平均轨迹偏差降低68%，表现出高精度与对外部干扰的良好补偿能力。
原文摘要 · Abstract (English)
The research presents an automated method for determining the trajectory of an unmanned aerial vehicle (UAV) for wind turbine inspection. The proposed method enables efficient data collection from multiple wind installations using UAV optical sensors, considering the spatial positioning of blades and other components of the wind energy installation. It includes component segmentation of the wind energy unit (WEU), determination of the blade pitch angle, and generation of optimal flight trajectories, considering safe distances and optimal viewing angles. The results of computational experiments have demonstrated the advantage of the proposed method in monitoring WEU, achieving a 78% reduction in inspection time, a 17% decrease in total trajectory length, and a 6% increase in average blade surface coverage compared to traditional methods. Furthermore, the process minimizes the average deviation from the optimal trajectory by 68%, indicating its high accuracy and ability to compensate for external influences.
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