Wind Turbine Blade Inspection with Drone Camera - Autonomous flying

the autonomous drone system for wind turbine blade inspection represents a significant leap forward in renewable energy maintenance. Combining state-of-the-art drones, onboard sensors, and advanced payloads, this system empowers the industry to maintain its assets efficiently, safely, and cost-effectively, ultimately contributing to the sustainable production of clean energy for generations to come.

The system includes:

Drone, remote control, and GNSS base station: by using RTK technology, the drone can be position at centi-meter level accuracy. The drone is also equipped with advanced flight control systems, GPS navigation, and real-time communication capabilities. 

Onboard sensors and controller: 

• Laser Range Finder: The laser range finder is a critical sensor that helps the drone maintain a safe distance from the wind turbine blades and trigger the camera to take the photos when the blade is detected. It ensures that the inspection process is carried out with precision and safety in mind.

• Drone-Based Controller: This controller is the brain behind the drone’s autonomous flight. It processes data from various sensors, executes flight plans, and ensures that the drone follows the predetermined inspection route accurately. It also incorporates obstacle avoidance algorithms to guarantee safe navigation;

Payloads:

• Cameras: High-resolution cameras capture detailed images of the wind turbine blades. These images provide essential visual data for assessing the condition of the blades, detecting defects, and identifying areas in need of maintenance or repair.

• LiDAR (Light Detection and Ranging): LiDAR sensors play a crucial role in creating 3D models of the wind turbine and its surroundings. By emitting laser pulses and measuring their return times, LiDAR sensors generate precise, detailed maps that facilitate accurate assessments of the turbine’s condition.

Work station:

The work station is used for wind farm and wind turbine information management. It is also the processer for flight planning during static inspection, and the embeded AI algorithm can also analyze the images captured and generate the reports.