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.
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