Core Research Areas
Core Research Areas
Deep learning-based Predictive Maintenance
Computer Vision for Wind Turbine Health Management
Digital Twin Framework for Fault Diagnosis and Prognosis
Current Research Statements
Development of a decision support system for wind turbine condition monitoring and maintenance.
Wind Turbine Gearbox Prognostics based on Multimodal AI.
Development of advanced machine learning algorithms for wind turbine condition monitoring, utilizing data from multiple sensors.
Development of a cloud-based platform for wind turbine condition monitoring, allowing remote access to real-time data.
Investigation of the impact of wind turbine blade damage on the overall system performance, and the development of methods to detect and diagnose blade damage.
