Researchers at the Bydgoszcz University of Science and Technology are developing the first hybrid system for monitoring wind turbines. This innovative solution combines measurement data with machine learning techniques to extend the lifespan and improve the efficiency of wind turbines.
The project is being carried out at the Faculty of Civil and Environmental Engineering and Architecture in collaboration with Eurowind Energy.
The collaboration aims to develop innovative solutions in the field of renewable energy.
One of these solutions is the first hybrid system for monitoring and diagnosing the technical condition of wind turbines. It will combine measurement data with machine learning techniques to enhance turbine efficiency, reduce mechanical wear, and enable early detection of potential failures.
The system analyzes a wide range of parameters, including vibrations and tilts, rotor and generator rotational speed, blade pitch angles, turbine yaw deviation relative to wind direction, and environmental conditions such as wind, temperature, and icing — all of which allow for an accurate assessment of the turbine’s technical state.
Thanks to the implemented models, the system not only evaluates the current technical condition of the turbine but also predicts its wear and potential future failures. Moreover, the vibration damping systems developed as part of the project could significantly extend the lifespan and improve the efficiency of wind turbines, emphasizes Dr. hab. Eng. Maciej Dutkiewicz, Dean of the Faculty of Civil and Environmental Engineering and Architecture at Bydgoszcz University of Science and Technology, an expert in technical diagnostics and dynamic system modeling.
This project is more than just an academic endeavor – it is a direct contribution to Poland’s energy transformation.
Source: Bydgoszcz University of Science and Technology
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