Induction motor model validation using fast fourier transform and wavelet tools
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abstract
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This paper presents a comparative validation for electric stator and rotor faults through an induction-motor modeling utilizing Park Instantaneous Space Phasor (ISP) during stator current analysis and fast Fourier Transform (FFT2) to identify the fault spectrum and the band spectral density of wavelet coefficients using multi-resolution analysis (MRA). The spectral analysis identifies the fault signature modifying the sample frequency in the data acquisition system. The wavelet analysis maintains a constant sample frequency using MRA, which provides redundant information to identify the faults. Furthermore, the MRA analysis of ISP stator currents helps to identify small incipient faults choosing a threshold between the healthy and faulty machine. The cases considered are stator and rotor electric faults, which are modeled by means of parametric variations. In Spite of its simplicity, the model provides useful information for fault identification. © 2013 IEEE.
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Fault detection; Frequency analysis; Induction motor; ISP; MRA; Wavelet analysis Electric machinery; Fast Fourier transforms; Fault detection; Induction motors; Power electronics; Rotors (windings); Spectral density; Stators; Wavelet analysis; Data acquisition system; Fault identifications; Frequency Analysis; Induction motor model; ISP; MRA; Parametric variation; Wavelet coefficients; Electric drives
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