Wear prediction and reliability analysis of main bearing under multi-source uncertainties

Abstract

The main bearing wear is often affected by multi-source uncertainties, which also challenges the prediction of bearing wear. In this paper, a method of main bearing wear prediction and reliability analysis under multi-source uncertainties is proposed. Firstly, the multi-flexible body friction dynamics model of the main bearing is established, in which the mixed lubrication behavior of the main bearing is described by the average Reynolds equation and Greenwood-Tripp rough contact theory. Then, based on Latin hypercube sampling, the sample data of the key uncertainties of the main bearing are obtained and substituted into the multi-flexible body friction dynamics model, thus the wear data of the main bearing are obtained, and the distribution characteristics of the wear of the main bearing are obtained through statistics. Finally, the relationship between multi-source uncertainties and wear data is established based on the surrogate model, and the reliability data and lifespan of the main bearing are obtained based on the interference theory. Through the analysis, it is found that: (1) The maximum cyclic wear depth of the flexible body model is about 2.81 times that of the rigid body model. (2) The calculation error of the main bearing wear prediction surrogate model is about 10%. (3) The maximum cyclic wear depth under multi-source uncertainties satisfies the three-parameter Weibull distribution. (4) Under the influence of multi-source uncertainty, the B10 life of main bearing is 1.64 × 10⁴ h.