Non-invasive method for rotor bar fault diagnosis in three-phase squirrel cage induction motor with advanced signal processing technique

The condition monitoring of the rotor bar in the squirrel cage induction motors (SCIMs) is performed with various contact methods and non‐contact methods. The various contact methods are zero sequence current spectrum measurement, non‐uniform time resampling of current, motor current spectrum analysis, vibration measurement, etc. Non‐contact methods are infrared thermography, stray flux measurement, acoustic emission measurement, temperature measurement, etc. The contact methods execute via vibration, instantaneous frequency, rotor speed and flux signal analysis. Whereas, non‐contact method accomplishes via acoustic, current, temperature and stray flux measurement. The existing methods suffer from the influence of adjoining machines, surrounding environmental changes; require human expertise to mount sensors and analysing the signals. In this paper, a novel low‐cost and non‐invasive method proposed for rotor bar fault identification in SCIMs with Software Phase Locked Loop (SPLL). The proposed method uses a high‐frequency signal projected on the motor and the reflected signal captured. The captured signal analysed by Fast Fourier Transform (FFT) and Wavelet transforms to identify the fault. The performance of these transforms compared in term of accuracy to identify the rotor bar faults of SCIM. The experimental results show that the proposed method achieves better accuracy than the existing methods..

Abstract licence: CC BY-NC-ND

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