Autonomous System for the Inspection of Wind Turbines Using Multispectral Imaging and Physical and Electrical Characterisation.
Data
Acronym: AEROGENIA
Reference: CPP2022-009933
Partners: Instituto Tecnológico y de Energías Renovables (ITER), Universidad Politécnica de Madrid (UPM) and Universidad de Alcalá (UAH).
Duration: 2023-2026
Budget:709,164.88 €
Co-Financing: Public-Private Collaboration 2022. State Plan for Scientific and Technical Research and Innovation 2021-2023. Ministry of Science and Innovation. Project CPP2022-009933 funded by MCIN/AEI / 10.13039/501100011033 and by the European Union NextGenerationEU/ PRTR.
Project overview
The main objective of this project is to optimise the predictive maintenance of the elements of a wind turbine, with a special focus on the blades, which are critical components in the operation of wind energy installations. To achieve this objective, work will be carried out on the development, validation and industrialisation of a comprehensive system for diagnosing defects in wind turbines.
A virtual replica of the wind turbine will be built in which its electrical and physical behaviour will be characterised in order to identify possible defects and pathologies of the wind turbines in advance. Using artificial intelligence techniques, the ideal behaviour of the wind turbine will be modelled and by continuously evaluating its response in real time, deviations indicating performance losses will be detected.
By correlating the electrical and physical variables entered into the digital twin with typical wind turbine defects and issues, it will be possible to determine when a more detailed visual inspection is required and in which area of the wind turbine it is occurring.
This event will trigger the take-off of a drone that will perform an autonomous inspection of the wind turbine by acquiring multispectral images. Once on the ground, the data will be transmitted to a processing server where a previously trained wind turbine anomaly detection model will automatically identify the type of defect and its severity.
The information obtained through this process will be displayed on a specifically designed visualisation interface, which will allow the operator to see in real time both the electrical response of the wind turbine and a complete image of the wind turbine in the visible and infrared (thermal) spectra. This interface will also automatically display any defects detected during the process.
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