2134/23234
Raed Ibrahim
Raed
Ibrahim
Simon Watson
Simon
Watson
Advanced algorithms for wind turbine condition monitoring and fault diagnosis
Loughborough University
2016
Wind turbine
Generator
Condition monitoring
Current signature
Fault signature
Fault detection
Diagnosis
Mechanical Engineering not elsewhere classified
2016-11-21 14:23:32
Conference contribution
https://repository.lboro.ac.uk/articles/conference_contribution/Advanced_algorithms_for_wind_turbine_condition_monitoring_and_fault_diagnosis/9549533
The work undertaken in this research focuses on advanced condition monitoring and fault detection methods for wind turbines (WTs). Fourier Transform (FFT) and Short Time Fourier transform (STFT) algorithms are proposed to effectively extract fault signatures in generator current signals (GCS) for WT fault diagnosis. With this aim, a WT model has been implemented in the MATLAB/Simulink environment to validate the effectiveness of the proposed algorithms. The results obtained with this model are validated with experimental data measured from a physical test rig. The detection of rotor eccentricity is discussed and conclusions drawn on the applicability of frequency tracking algorithms. The newly developed algorithms are compared with a published method to establish their advantages and limitations.