By Topic

Motor bearing fault diagnosis by a fundamental frequency amplitude based fuzzy decision system

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
$33 $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)
G. Goddu ; Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA ; Bo Li ; Mo-Yuen Chow ; J. C. Hung

The dynamic performance of motor bearings is highly influential on the performance of the entire motor system. More specifically, the presence of bearing defects often results in reduced efficiency, or even severe damage, of the motor under consideration. In order to determine when it is necessary to take a motor off-line for preventative maintenance, these faults must be diagnosed. In this paper, the frequency spectrum of the bearing vibration signal is analyzed using a fuzzy logic fault diagnosis methodology. The preliminary results show that fuzzy logic can be used for accurate bearing fault diagnosis if the input data is processed in an advantageous way

Published in:

Industrial Electronics Society, 1998. IECON '98. Proceedings of the 24th Annual Conference of the IEEE  (Volume:4 )

Date of Conference:

31 Aug-4 Sep 1998