Static eccentricity fault detection of induction motors using MVSA, MCSA and discrete wavelet transform (DWT)
2017
The aim of the present paper is to diagnose the mechanical faults in induction motors. We have chosen this part in order to contribute to the diagnosis of electrical machines. The raising of stator current allows detecting the fatigue of the machine failure. The manner of the treatment decides the efficiency of the applied technique. We have examined the static eccentricity fault by a vibration signal analysis. Motor vibration signature analysis (MVSA) is a large part for detecting faults in electric machines. The use of motor current signature analysis (MCSA) gives adequate information about the fault type. In this paper, the fast Fourier transforms (MCSA-FFT) and the discrete wavelet transform (MCSA-DWT) are applied to analyze the stator current. In this study a comparison has been made between the three methods which we have used to arrive at a good decision about a static eccentricity fault. In this present paper, experimental results were analyzed under a healthy and faulty machine.
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