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This paper proposes an original combination of Power Spectrum Density estimation(PSD) and Support Vector Machines(SVMs) to diagnose and detect broken-rotor-bar faults in induction motor under different levels of load. The PSD estimate is used for feature extraction and aim to identify the descriptors that show high variability between different classes and thus would help distinguish between them. This paper analyses three different spectral decomposition methods applied to induction machine stator current, namely Welch, Burg and Multiple Signal Classification(MUSIC). Based on different power spectral estimation concepts, the frequency resolution, variance and detection capability are different for each method according to the set of parameters used. In this paper, the strategy of multiclass SVMs-based classification is applied to perform the faults recognition. The proposed methodology aims to determine …