Application of wavelet transform for wind energy generator diagnostic

In this paper, we propose a method for monitoring a wind energy generator using wavelet transform, aiming to enhance fault detection and localization capabilities. This method involves applying wavelet transform to analyze the stator and rotor currents, enabling the identification and precise localization of faults that may arise during operation. The wavelet transform, known for its ability to process non-stationary and transient signals, is particularly suited to capturing the dynamic behavior of electrical currents in wind energy systems. After a detailed presentation of the fundamental characteristics and advantages of the wavelet transform in fault analysis, we focus on implementing specific algorithms, namely those of Morley, Gabor, and Wigner-Ville. These algorithms are applied to classify various types of faults affecting the stator and rotor currents, providing a comprehensive diagnostic framework. The proposed approach not only contributes to early fault detection but also aids in minimizing downtime and improving the overall reliability and efficiency of wind energy generators.