Enhanced ESPRIT Algorithm for Optimal Wind Turbine Fault recognizing

Saad Chakkor, Mostafa Baghouri, Abderrahmane Hajraoui


Fault Recognition occupies a prominent place in the advanced electrical power production systems. The wind turbine machine requires an on-line regular maintenance to guarantee an acceptable lifetime and to maximize productivity. In objective to implement a fast, proactive condition monitoring, ESPRIT method seems the correct choice due to its robustness in ameliorating the frequency and amplitude discrimination. However, it has a very complex calculation to be implemented in real time. To address this problem, a Fast-ESPRIT algorithm that combined the IIR band-pass filtering technique, the decimation technique and the original ESPRIT method were employed to enhance extracting accurately frequencies and their magnitudes from the wind stator current. The proposed algorithm has been evaluated by computer simulations with many fault scenarios. Study results demonstrate the performance of Fast-ESPRIT allowing fast and high resolution harmonics identification with minimum computation time and less memory cost.

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