Analytical and experimental investigation of vibration characteristics induced by tribofilm-asperity interactions in hydrodynamic journal bearings

Vibration analysis is an effective approach to condition monitoring of hydrodynamic journal bearings. However, the analysis is largely based on the understanding of asperityasperity interactions due to severe wears in the late phase of bearing lifetime. It often provides very tight leading time for maintenance actions. Aiming at developing effective techniques for early wear monitoring, this paper investigates the excitation mechanisms and contributions of Tribofilm-Asperity Interaction (TAI) that occurs in the hydrodynamic lubrication regime of journal bearings. Analytical expressions for the microscopic pressure fluctuations with respect to the surface topography are derived using the perturbation techniques. The Spatial Power Spectral Density (SPSD), a feature of the non-Gaussian roughness surfaces for early wear, is used to analyse the microscopic pressure fluctuations. The effect of the SPSD and operating conditions on the random excitation are evaluated through numerical simulations. The bandwidth of such random excitation depends on the SPSD of dynamic asperities and rotational speeds simultaneously. The excitation intensity increases when the standard deviation or correlation length of the surface parameters increases. These agree well with the measurements for wide bearing conditions including different degrees of wears. This new efficient analysis and insightful findings provide new understanding for characterising noisy vibration signals for early wear monitoring of journal bearings. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

Vibration analysis is an effective method for monitoring the condition of hydrodynamic journal bearings, providing tight maintenance deadlines. This study investigates the excitation mechanisms and contributions of Tribofilm-Asperity Interaction (TAI) in the lubrication regime, analyzing microscopic pressure fluctuations using Spatial Power Spectral Density (SPSD) and evaluating the effects of operating conditions through numerical simulations.