Differentiation of Journal Bearing Friction States under varying Oil Viscosities based on Acoustic Emission Signals

For diagnosis and predictive maintenance of mechatronic systems, monitoring of bearings is essential. An integral component for this is the determination of the bearing friction condition. Hydrodynamic journal bearings experience three basic types of friction states: fluid, mixed and solid friction, whereas the last two types cause mechanical wear.This paper deals with the differentiation of these three basic types of journal bearing friction conditions under several rotational speed, load and oil viscosity combinations based on acoustic emission (AE) signals. The aim of this work is to show that it is possible to detect various oil viscosities under same loads and rotational speeds with AE features. An already developed classifier [1], which is trained and tested under various rotational speed and load combinations, can then be improved by training and testing it under several oil viscosities.Different oil viscosities were generated by varying the oil temperature. A special test environment is introduced for this purpose. The actual friction state was verified by the contact voltage (CV) between shaft and bearing [2].