Experimental study demonstrates reliable detection of broken outer-cage bars in double-cage induction motors during startup, highlighting discrete wavelet transforms over steady-state analysis.
Unlike single-cage rotor fault detection, fast Fourier transform (FFT)-based steady-state spectrum analysis techniques can fail to detect outer-cage faults in double-cage induction motors due to the small outer-cage current under running conditions. Double-cage motors are typically employed in applications that require loaded starts. This makes the outer cage vulnerable to fatigue failure since it must withstand the high starting current and long startup time frequently. However, there are only a few publications that investigate detection techniques specifically for double-cage motors. In this paper, considering that the influence of the faulty outer cage is strong at startup due to the large outer-cage current, detection of outer-cage faults under the startup transient is investigated. A discrete-wavelet-transform-based method is proposed as a viable solution to the detection of outer-cage faults for double-cage motors. An experimental study on fabricated copper double-cage induction motors shows that the proposed method provides sensitive and reliable detection of double-cage rotor faults compared to FFT.
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Antonino‐Daviu et al. (2012) studied this question.
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