Physics-Informed Data-Driven Methods for Condition Monitoring of Wind Turbine Generators

Wind energy plays an important role in UK ambitious plan for Net Zero Future by 2050. It demands breakthroughs in condition monitoring technologies to make wind energy more competitive by lowering its operation and maintenance costs. This project aims to bridge the gap between academic and industrial research on condition monitoring and predictive maintenance of wind turbine generators and develop cost-effective methods to be demonstrated in real-world applications. The project is funded by Royal Academy of Engineering (RAE) Industrial Fellowship Project and in collaboration with industry company ONYX.