Modelling non-Gaussian surfaces and misalignment for condition monitoring of journal bearings

Jiaojiao Ma, Chao Fu, Hao Zhang, Fulei Chu, Zhanqun Shi, Fengshou Gu, Andrew D. Ball

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)


In the hydrodynamic lubricated journal bearing system, the surface roughness and angular misalignment are two critical factors that affect bearing’s performance. In this paper, the coupled effects of different non-Gaussian properties and misalignments are investigated on the performance of journal bearings. Christensen’s stochastic model is extended by improving the probability density function of random roughness heights, which incorporates the Gram-Charlier expansion including skewness and kurtosis. In comparison with a Gaussian surface, the non-Gaussian rough surface has more significant influence on the bearing static performance. The negative skewness and large kurtosis increase the load capacity and decrease the friction coefficient. According to the simulations and experiments, non-Gaussian properties have more impact on the performance than misalignment when the journal bearing is operated in hydrodynamic lubrication regime based on different pressure distributions and vibration responses. These novel findings provide the basis for monitoring the conditions of hydrodynamic journal bearings.
Original languageEnglish
Article number108983
Number of pages15
Early online date7 Jan 2021
Publication statusPublished - 1 Apr 2021


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