Scheduled System Maintenance:
On Wednesday, July 29th, IEEE Xplore will undergo scheduled maintenance from 7:00-9:00 AM ET (11:00-13:00 UTC). During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Induction motor asymmetrical faults detection using advanced signal processing techniques

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Benbouzid, M.E.H. ; UPJV/ESIEE, Unite Mixte de Recherche, Amiens, France ; Nejjari, H. ; Beguenane, R. ; Vieira, M.

Preventive maintenance of electric drive systems with induction motors involves monitoring of their operation for detection of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of the system. Intensive research effort has been for sometime focused on the motor current signature analysis. This technique utilizes the results of spectral analysis of the stator current. Reliable interpretation of the spectra is difficult, since distortions of the current waveform caused by the abnormalities in the drive system are usually minute. In the present investigation, the frequency signature of some asymmetrical motor faults are well identified using the fast Fourier transform (FFT), leading to a better interpretation of the motor current spectra. Laboratory experiments indicate that the motor current signature FFT-based analysis, with the proposed approach, is still a reliable tool for induction motor asymmetrical faults detection

Published in:

Energy Conversion, IEEE Transactions on  (Volume:14 ,  Issue: 2 )