High Resolution Identification of Wind Turbine Faults Based on Optimized ESPRIT Algorithm

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Saad Chakkor 1,* Mostafa Baghouri 1 Abderrahmane Hajraoui 1

1. University of Abdelmalek Essaâdi, Faculty of Sciences, Department of Physics, Communication and Detection Systems Laboratory, Tetouan, Morocco

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2015.05.04

Received: 11 Dec. 2014 / Revised: 23 Jan. 2015 / Accepted: 3 Mar. 2015 / Published: 8 Apr. 2015

Index Terms

Spectral Estimation, ESPRIT, Real Time, Diagnosis, Wind Turbine Faults, Band-Pass Filtering, Decimation


Many researchers employ ESPRIT method as robust detection tool to identify fault frequency and amplitude in induction machines. However, this algorithm presents some limitation in terms of computational time and required data memory size. This drawback makes this technology unusable in real time diagnosis application. In the fact that wind turbine machine necessitates an on-line regular maintenance to guarantee an acceptable lifetime and to maximize its productivity. Thus, an improved version of ESPRIT-TLS method has been proposed and simulated to extract accurately fault frequencies and their magnitudes from the wind stator current with minimum computation time and less memory cost. The proposed approach has been evaluated by computer simulations under many fault kinds. Study outcomes prove the benefits and the performance of Fast-ESPRIT.

Cite This Paper

Saad Chakkor, Mostafa Baghouri, Abderrahmane Hajraoui,"High Resolution Identification of Wind Turbine Faults Based on Optimized ESPRIT Algorithm", IJIGSP, vol.7, no.5, pp.32-41, 2015. DOI: 10.5815/ijigsp.2015.05.04


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