Induction Motor Bearing Fault Analysis Using a Root-MUSIC Method

This paper describes a new diagnosis approach, the Root-Multiple Signal Classification (MUSIC) (RM) method, for identification of the progressive cracking in the bearing of induction motors. This approach has several advantages compared with the stator current spectral analysis using the conventiona...

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Bibliographic Details
Published in:IEEE transactions on industry applications 2016-09, Vol.52 (5), p.3851-3860
Main Authors: Boudinar, Ahmed Hamida, Benouzza, Noureddine, Bendiabdellah, Azeddine, Khodja, Mohammed-El-Amine
Format: Article
Language:English
Subjects:
Bearing
cracks
Fault diagnosis
frequency band
Harmonic analysis
induction motor
Induction motors
Matrix decomposition
power spectral density (PSD)
Root-Multiple Signal Classification (MUSIC)
Signal resolution
spectral analysis
stator current
Stators
Time-frequency analysis
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Summary:This paper describes a new diagnosis approach, the Root-Multiple Signal Classification (MUSIC) (RM) method, for identification of the progressive cracking in the bearing of induction motors. This approach has several advantages compared with the stator current spectral analysis using the conventional Periodogram method. Indeed, the main advantage of this approach is its very good frequency resolution for a very short acquisition time, something impossible to achieve with the conventional method. However, in order to reduce the computation time, which is the main drawback of the RM method, this method will be applied to only a specified frequency band; one that carries information about the sought fault. Experimental results show the effectiveness of the RM method on the reliability of the incipient bearing fault detection.
ISSN:0093-9994
1939-9367
DOI:10.1109/TIA.2016.2581143