Detection of lubrication starved bearings in electrical motors by means of vibration analysis

The detection of improperly lubricated bearings from vibration patterns is a difficult task especially when records from short operating periods are available. This is exactly the case of end-quality assessment systems. This problem has been addressed by applying both cyclostationary analysis and spectral kurtosis for the selection of a frequency band in which variations in vibration patterns are most expressed. The approach was evaluated on a test-set comprising 63 electrical motors with fault-free and 21 with improperly lubricated bearings. The results reveal that improper lubrication is expressed as increase in the spectral components at bearing cage and ball spin frequency.