Prediction of Remaining Useful Life of Passive and Adjustable Fluid Film Bearings Using Physics-Based Models of Their Degradation

Systems for online prediction of remaining useful life (RUL) of technological equipment, and, in particular, fluid film bearings, are usually based on the analysis of a large amount of data received from the operated objects. In practice, formation of a data set meeting the size and quality requirements often encounters a number of difficulties. The work presents the approach to the possible overcoming of such difficulties through the use of physics-based models of degradation of fluid film bearings. The most common reasons for replacing them in rotating machines are considered as the criteria for the end of the service life. They include achievement of the wear limit in accordance with the current standard, and disruption of the bearing surfaces after reaching the material’s fatigue strength limit. The work focuses mainly on the last factor and demonstrates mathematical and numerical simulation models of rotor-bearing systems considering this phenomenon and allowing generating data on the bearing degradation process. The generated data is used to train a predictive model that estimates online the current state and RUL of the bearing. In addition, the proposed physics-based models also allow to evaluate the impact of the adjustable design of the fluid film bearings on their expected service life. The variable parameters of the adjustable bearings are also taken into account by the proposed predictive model. The work shows the results of numerical studies demonstrating the change in the service life taking in account the adjustable bearing parameters.