Dynamic Trajectory Adaptation for Efficient UAV Inspections of Wind Energy Units

TL;DR

This paper introduces an automated UAV trajectory planning method for wind turbine inspections that significantly reduces inspection time and improves coverage accuracy, enhancing efficiency and safety in wind energy maintenance.

Contribution

The paper presents a novel automated trajectory adaptation approach for UAV inspections of wind turbines, optimizing data collection and safety considerations.

Findings

78% reduction in inspection time

17% decrease in trajectory length

6% increase in blade surface coverage

Abstract

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.