Authors: Joshua Zander, Angel Rodriguez, Mason Davis, Edwin Nazario Dejesus, Mohammad Shekaramiz, Mohammad A S Masoum, Abdennour Seibi
Mentors: Mohammad Shekaramiz
Insitution: Utah Valley University
The proposed approach of using computer vision and autonomous drones for inspecting small wind turbines is a significant step towards improving the efficiency and safety of wind turbine inspections. The use of DJI Mini 3 Pro and Matrice 300 drones in conjunction with DJI’s Mobile SDK, which allows for programmed flights, enables the drones to fly autonomously and capture high-quality images of the wind turbines. The images are then processed using object detection with YOLOv8, which can accurately detect the turbines. Navigation is based on both GPS and object detection, which ensures that the drones can navigate accurately and avoid any obstacles. The proposed approach is expected to reduce the cost and time required for wind turbine inspections, while also improving the accuracy of the inspection process. This approach can be used to inspect wind turbines in remote locations, which are difficult to access, and can help identify any issues with the turbines before they become major problems.
The proposed approach has the potential to revolutionize the wind energy industry by making wind turbine inspections more efficient and cost-effective. The use of computer vision and autonomous drones can help reduce the need for human intervention in the inspection process, which can be dangerous and time-consuming. The proposed approach can also help improve the accuracy of the inspection process by providing high-quality images of the turbines. This can help identify any issues with the turbines before they become major problems, which can help reduce the risk of accidents and improve the safety of the wind energy industry.