Research Interests

• Wind turbine condition monitoring and fault detection; 
•  Aeroacoustics.

Biography

09/2019 to now: PhD Candidate    
Wind Energy section, Faculty of Aerospace Engineering, Delft University of Technology.         
08/2016 to 06/2019: MSc in Control Science and Engineering 
Department of Automation and Measurement & Control, College of Engineering,    
Ocean University of China, Qingdao, China.
09/2012 to 06/2016: BSc in New Energy Science and Engineering     
Department of New Energy, College of energy and electrical engineering,    
Hohai University, Nanjing, China. 

Research Description

Wind Turbine Blade Condition Monitoring and Fault Detection Using Aerodynamic Noise
Wind turbine noise is an issue for the promotion of wind energy, and current research about how to reduce the noise of the wind turbine gives more and more detailed and clear mechanisms for the noise generation and propagation. One interesting thing is that the noise is also affected by the blade conditions, which provides a potential metric to detect the blade faults/damage. In this research, a new approach based on the wind turbine aerodynamic noise measurement is attempted to apply to wind turbine blade damage detection and condition monitoring. In the first stage, the ideal and standard airfoils experiments can be implemented to find the noise characteristics which are sensitive to damage and corresponding damaged types, levels and positions and then a small-scale wind turbine is used for condition monitoring analysis. Furthermore, the proposed approach will be verified in a real wind farm.

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