Researchers from ITER’s Robotics and Automation team began test flights to validate the methodology to be used in the acquisition of thermal images in wind turbines.
The AEROGENIA project is in the initial phase, in which work is being done to confirm that the proposed methodology fits the environmental conditions and the specifications of the wind turbine models under study. Researchers from ITER’s Robotics and Automation team have started test flights to validate the flight methodology for the acquisition of thermal images in wind turbines.
During the tests, a drone equipped with a high-precision thermal camera (Zenmuse H20T) was used to capture multispectral data from wind turbines. The main objective was to establish a robust methodology that allows the accurate detection of defects or anomalies in wind turbines, which are difficult to identify with conventional methods.
The activity included a precise review of the technical requirements, the definition of the control points to determine the flight path and speed, and the verification and validation of the acquired data with the tested methodology. Once the methodology is confirmed, it will be ensured that the system can operate autonomously and effectively in real conditions.
The ITER team continues to work on refining the technology and conducting further tests to ensure the feasibility and efficiency of the system. Collaboration between engineers, technicians and computer vision specialists is critical to the continued success of this innovative project.”
The AEROGENIA project addresses the growing importance of wind power generation in Spain and the need for efficient management of wind turbine maintenance. The project focuses on the optimization of predictive maintenance of wind turbines, especially blades, through the development of a comprehensive system for defect diagnosis. Making use of artificial intelligence techniques and a digital twin, the project will make it possible to anticipate failures, perform autonomous inspections using drones, and visualize the health of the wind turbine in real time, thus contributing to maximize the availability and efficiency of wind power generation in Spain. This project is funded by the Ministry of Science and Innovation through the State Research Agency /10.13039/501100011033 and by the European Union NextGenerationEU/PRTR.
