Future of Information and Communication Conference (FICC) 2024
4-5 April 2024
Publication Links
IJACSA
Special Issues
Future of Information and Communication Conference (FICC)
Computing Conference
Intelligent Systems Conference (IntelliSys)
Future Technologies Conference (FTC)
International Journal of Advanced Computer Science and Applications(IJACSA), Volume 5 Issue 4, 2014.
Abstract: Electrical energy production based on wind power has become the most popular renewable resources in the recent years because it gets reliable clean energy with minimum cost. The major challenge for wind turbines is the electrical and the mechanical failures which can occur at any time causing prospective breakdowns and damages and therefore it leads to machine downtimes and to energy production loss. To circumvent this problem, several tools and techniques have been developed and used to enhance fault detection and diagnosis to be found in the stator current signature for wind turbines generators. Among these methods, parametric or super-resolution frequency estimation methods, which provides typical spectrum estimation, can be useful for this purpose. Facing on the plurality of these algorithms, a comparative performance analysis is made to evaluate robustness based on differents metrics: accuracy, dispersion, computation cost, perturbations and faults severity. Finally, simulation results in Matlab with most occurring faults indicate that ESPRIT and R-MUSIC algorithms have high capability of correctly identifying the frequencies of fault characteristic components, a performance ranking had been carried out to demonstrate the efficiency of the studied methods in faults detecting.
CHAKKOR SAAD, Baghouri Mostafa and Hajraoui Abderrahmane, “Performance Analysis of Faults Detection in Wind Turbine Generator Based on High-Resolution Frequency Estimation Methods” International Journal of Advanced Computer Science and Applications(IJACSA), 5(4), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050420
@article{SAAD2014,
title = {Performance Analysis of Faults Detection in Wind Turbine Generator Based on High-Resolution Frequency Estimation Methods},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.050420},
url = {http://dx.doi.org/10.14569/IJACSA.2014.050420},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {4},
author = {CHAKKOR SAAD and Baghouri Mostafa and Hajraoui Abderrahmane}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.