posted on 2016-11-21, 14:23authored byRaed Ibrahim, Simon Watson
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.
History
School
Mechanical, Electrical and Manufacturing Engineering
Published in
WindEurope Summit 2016
Citation
IBRAHIM, R.K. and WATSON, S.J., 2016. Advanced algorithms for wind turbine condition monitoring and fault diagnosis. Presented at the WindEurope Summit 2016, Hamburg, 27-29th Sept.
Publisher
Wind Europe
Version
VoR (Version of Record)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/