Approach for the Degradation of Hydrodynamic Journal Bearings based on Acoustic Emission Feature Change

For predictive maintenance of mechatronic systems, monitoring of bearings is essential. An important building block for this is the determination of the bearing's remaining useful lifetime (RUL). This paper deals with the possibility of estimating the journal bearing's RUL by determining the actual wear depth based on acoustic emission (AE) feature change over the lifetime. The aim of this work is to find the correlation between the AE feature and the actual wear depth, which is a direct indicator for the RUL. The wear depth limit is the bearing clearance value and indicates the end of the lifetime. Time domain features as well as features in the frequency domain have been applied to identify the journal bearing friction condition. The correlation of the AE feature change with the journal bearing wear depth is afterwards shown by conducting endurance tests. Tactile surface measurements were done to verify this relationship. A regression model can be developed to calculate the actual wear depth based on the actual and the elapsed AE features. This is the first known work that has illustrated the AE feature drift in one direction with increasing wear depth for hydrodynamic journal bearings. The results show that with this method an online determination of the actual wear depth is possible.