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This paper proposes an original combination of Stationary Wavelet Packet Transform (SWPT) and Multiclass Wavelet Support Vector Machines (MWSVM) to detect broken rotor bar (BRB) in induction motor (IM). The SWPT is used for feature extraction under lower sampling rate. MWSVM is developed to perform the faults recognition. Different binary Multiclass SVM strategies are compared with various wavelet kernel functions in terms of classification accuracy, training and testing complexity. The experimental results show that the proposed method is able to detect the faulty conditions with high accuracy.