Feature Extraction for the Prognosis of Electromechanical Faults in Electrical Machines through the DWT

Recognition of characteristic patterns is proposed in this paper in order to diagnose the presence of electromechanical faults in induction electrical machines. Two common faults in this type of machines are considered; broken rotor bars and mixed eccentricities. The presence of these faults leads to the appearance of frequency components following a very characteristic evolution during the startup transient and other transients through which the machine operates. The identification and extraction of these characteristic patterns through the Discrete Wavelet Transform (DWT) has been proven to be a reliable methodology for diagnosing the presence of these faults, showing certain advantages in comparison with the classical FFT analysis of the steady-state current. In the paper, a compilation of healthy and faulty cases are presented; they confirm the validity of the approach for the correct diagnosis of a wide range of electromechanical faults. Keywords—electric machines, fault diagnosis, wavelet tramsform, broken bars, eccentricties

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