Condition monitoring system for characterization of electric motor ball bearings with distributed fault using fuzzy inference tools
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
The present work shows a condition monitoring system applied to electric motors ball bearings. Unlike most of the previous work on this area, which is mainly focused on the location of single-point defects in bearing components – inner and outer races, cage or ball faults -, this research covers wide range irregularities which are very often more difficult to analyse. In addition to traditional techniques like vibration and current signals, high frequency current bearing pulses and acoustic emissions are also analysed. High frequency bearings current pulses are acquired using motors especially modified. This modification isolates ball bearings from the motor stator frame, except for a bearing housing single point connected to ground through a proper cable where the pulses signal is measured. A multivariable fuzzy inference analysis approach is presented to get around the diagnosis difficulty.
CitationNavarro, L. [et al.]. Condition monitoring system for characterization of electric motor ball bearings with distributed fault using fuzzy inference tools. "EEE Instrumentation and Measurement Technology Conference. Proceedings", 06 Maig 2010, p. 1159-1163.