The production capacity of installed wind power greatly increases in worldwide. Hence the interest is focused on the reliability and efficiency of wind turbines; then to reduce the production cost and increase the yield. The main objective of our research in this work is to diagnose wind system. We presented a state of the art of diagnosis approach applied on wind turbines and various occurred faults which should be detected and isolated in the wind turbine parts. After that, an overview on this proposed solution for wind turbines, which opted for a diagnostic strategy based on support vector machines (SVM). A Benchmark of a wind power of 4.5 MW with faults on sensors, actuators and the systems was presented. Defects of the Benchmark are in the pitch system, the drive system, the generator and the converter. We tested then the effectiveness of the used method by visualizing simulation results of diagnosis in two different scenarios.
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