In this study, a novel technique for the autonomous visual inspection of rotating wind turbine rotor blades utilizing an unmanned aerial vehicle (UAV) was developed. This approach addresses the challenges presented by the dynamic environment at hand and the requirement of maintaining a safe distance from the moving rotor blades. The application of UAV-based inspection techniques mitigates these dangers and the expenses associated with traditional wind turbine inspection methods which involve halting normal wind farm operations. Our proposed system incorporates algorithms and sensor technologies. It relies on a light detection and ranging (LiDAR) sensor system, an inertial measurement unit, and a GPS to accurately identify the relative position of the rotating wind turbine with respect to the UAV's own position. Once this position is determined, a non-destructive visual analysis of the rotating rotor blades is performed by generating a suitable trajectory and triggering a camera fitted on a gimbal system as the blades approach. This new technique, built upon the existing research on UAV inspection of rotating wind turbines, has been empirically validated using data collected from real-world wind farm applications. This article contributes to the ongoing trend of enhancing the safety and efficiency of infrastructure inspection. It also presents a good base for future research, with potential applications for other types of infrastructure, such as bridges or power lines.

翻译：本研究提出了一种新技术，用于利用无人航空器对旋转的风力涡轮机转子叶片进行自主视觉检查。该方法解决了动态环境带来的挑战以及需与运动中的转子叶片保持安全距离的要求。应用基于无人机的检查技术可减轻这些危险，并避免传统风力涡轮机检查方法中因需停止正常风电场运营而产生的费用。我们提出的系统集成了算法与传感器技术，依托激光雷达传感器系统、惯性测量单元及全球定位系统，精确识别旋转涡轮机相对于无人机自身位置的相对方位。一旦确定该位置，通过生成合适的轨迹并在叶片接近时触发安装在云台系统上的相机，对旋转的转子叶片进行非破坏性视觉分析。这项新技术建立在现有关于无人机检查旋转风力涡轮机的研究基础上，并已通过从真实风电场应用收集的数据进行了实证验证。本文为提升基础设施检查安全性与效率的持续趋势做出了贡献，同时为未来研究提供了良好基础，其潜在应用可扩展至桥梁、电力线等其他类型基础设施。