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Advanced algorithms for wind turbine condition monitoring and fault diagnosis

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conference contribution
posted on 2016-11-21, 14:23 authored by Raed 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/

Acceptance date

2016-09-30

Publication date

2016

Notes

This is a conference paper.

Language

  • en

Location

Hamburg, Germany