Intelligent Ariel Robots for Autonomous Wind Turbine Blade Maintenance

One of the biggest issues regarding turbines is leading edge erosion (LEE) that is caused by the blades constantly hitting rain, snow, and ice at very high speeds. With the emerging issue of LEE on wind turbine blades, it is causing additional maintenance cost, which reduces the cost effectiveness of wind energy. I am working alongside a team in the Structures and Artificial Intelligence Lab to address the existing research gap in the automated leading edge erosion (LEE) maintenance process. The overall goal is to create a robotic arm attached to a UAV that will be able to sense the LEE affected areas and apply the LEE protection tape. Within this team, I am creating a proper, efficient, and lightweight end-effector design that will allow for the smooth application of the LEE protection tape. In this design I am incorporating a tactile pressure sensor. The purpose of this sensor will be to detect the deformation of the end effector as it is applying the protection tape to the wind turbine blade. Using this sensor will allow us to know how much force is needed to apply down onto the blade to ensure proper application of the tape.