Abstract
The frequency-domain analysis using the fast Fourier transform (FFT) for diagnosis of eccentricity fault has been widely used in squirrel-cage induction motor (IM). However, with the restriction of sampling frequency and time acquisition, FFT analysis could not provide ideal results under low levels of dynamic eccentricity (DE). In this paper, a combined use of the wavelet packet decomposition (WPD) and empirical mode decomposition (EMD) method is presented to diagnose the IM fault under low degrees of purely DE. The proposed method is based on the decomposition of apparent power signal and extracts the characteristic component. The fault severity factor (FSF) has been defined to evaluate the eccentricity severity. Simulation results using the finite element method (FEM) are tested to verify the effectiveness of the presented method under different load conditions.
Highlights
Three-phase squirrel cage induction motor plays an important role in industrial processing because of its low cost and high reliability
A high sampling frequency and a long-time acquisition are mandatory in order to obtain good results using the finite element analysis (FEA)
The combined use of wavelet packet decomposition (WPD) and empirical mode decomposition (EMD) has been proposed in order to extract the characteristic harmonic component related to the dynamic eccentricity (DE) fault
Summary
Three-phase squirrel cage induction motor plays an important role in industrial processing because of its low cost and high reliability. Airgap eccentricity is one of the most common types of fault occurring in the induction motor [1] This type of fault leads to unequal airgaps between the stator and rotor, which has a bad influence on the output rotation accuracy of the motor. Due to the transfer from the fundamental frequency to around DC, the fault signal can be detected clearly and the signal-to-noise ratio (SNR) can be improved [1] Because of these advantages, the spectrum of complex apparent power signature has been employed for diagnosis of the mixed airgap eccentricity in the induction motor [9]. Under the load, speed and voltage variations as well as the minor fault in the induction motor and the spectrum of the phase stator current using the FFT become distorted and may lead to inaccuracy detection of airgap eccentricity fault [8]. Precise determination of the DE levels and percentages of rated load are both discussed in this study
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