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In this paper, we perform an on-line fault diagnosis using high-resolution spectral analysis of the voltage between neu trals to detect rotor faults in Wound Rotor Induction Machine. For that, a Multiple Signal Classification (MUSIC) technique has been introduced in the 1M fault diagnosis world. MUSIC has the highest frequency resolution among all FFT-based methods, non parametric and parametric methods. Despite its effectiveness in improving the freqency resolution, MUSIC is computationally too complex to implement in real time and it takes a long computation time to find more frequencies by increasing the order of the frequency signal dimension. To address this problem, a zoom MUSIC algorithm (ZMUSIC) that combined the zoom technique and the MUSIC algorithm was proposed.We present the results obtained for real data to verify the proposed method for monitoring of Wound Rotor Induction Machine.