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induction motors, fault diagnosis, rotors, digital signal processing, spectral analysis
induction(27), motors(20), detection(15), fault(13), rotor(11), industrial(10), diagnosis(10), broken(10), electronics(9), systems(8)
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About this article
Date of Publication: 2019-05-31
Volume 19, Issue 2, Year 2019, On page(s): 61 - 68
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.02008
Web of Science Accession Number: 000475806300008
SCOPUS ID: 85066316496
Over the years induction motors have established an uncanny knack for providing a plethora of utilities in the industry, where the fault monitoring and detection has become necessary. Several techniques could be applied for the monitoring and identification of broken rotor bars when the motor is fed by a variable speed drive (VSD). Nevertheless, many of these methodologies detect this fault and other failures in the steady state condition, but this monitoring grow into more complicated analysis during the startup transient condition owing to the large number of harmonics, which the VSD insert to the current signal. The novelty of the proposed methodology is the application of the reassignment during the startup transient and the steady state conditions to identify one broken rotor bar in the induction motor. The proposed methodology is experimented with both, real and synthetic signals. The problems that Short Time Fourier Transform (STFT), shows for the identification of broken rotor bars are exhibited. The proposed methodology includes an automatic diagnosis (K-means algorithm), where the signal energy is used. The results show that the Reassigned Short Time Fourier Transform (RSTFT) technique and K-means methods are appropriated for the effective monitoring and diagnosis of one broken rotor bar in the induction motor during the startup and steady state conditions of operation.
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Digital Object Identifier: 10.3390/pr10010055 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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