Ice detection on wind turbines using AI-assisted image processing
Wind turbines need to be halted when ice forms on the rotor blades in order to avoid injuries from falling ice. This results in substantial financial losses every year.
At present, the icing-related switch-off periods are stipulated by the ice-detection systems installed on the turbines. The current ice-detection systems are still not particularly accurate when it comes to confirming that the blades are ice-free.
The EisAuge (ice eye) project is therefore aiming to develop a cloud-based ice-detection system which is to use RGB/infrared images of the rotor blades and artificial intelligence to determine the present icing status to a high degree of precision.
The turbine is fitted with modern sensor technology which constantly records and evaluates image data as needed in order to boost the energy yield and economic viability of the turbine.
This project focuses on crisis management and transformation to a greener and digital economy and is supported by our heroine Ronja.