Performance Prediction of Rolling Bearing Greases in Robotic Applications

With the widespread use of robots in industry, more and more bearings operate under oscillating conditions with grease lubrication. However, the influence of grease parameters on the lubrication performance of bearings at different oscillation angles and frequencies has not yet been fully investigated. In this project, bearing tests, rheological measurements and simulations were carried out to investigate the suitability of greases for robotics. 8 types of greases were investigated at different frequencies and amplitudes. The frictional torque and microscopic representation of bearing wear were used to evaluate the lubrication performance. In addition, some verification experiments were carried out with different loads, bearing types and different amount of grease. Some rheological measurements were used to model the greases. These tests enabled the relationship between the rheological parameters and the lubrication performance of the greases in bearing tests. The selection criteria for lubricating greases under vibration conditions were first established. The rheological tests also formed the basis for the CFD simulation. With the help of a CFD simulation, it was possible to map the grease distribution in a real bearing, which can be used to calculate the friction loss. Thus, some experimental phenomena can also better explain the influence of the cage and the rotation of the ball on the grease distribution in future research. Finally, some common methods to improve the lubrication performance were tried. These include pre-shearing and bearing sealing.

The IGF project (20170 N) of the research association DGMK Deutsche Wissenschaftliche Gesellschaft für Erdöl, Erdgas und Kohle e.V., Überseering 40, 22297 Hamburg was funded by the Federal Ministry for Economic Affairs and Energy via the AiF within the framework of the programme for the promotion of joint industrial research (IGF) on the basis of a resolution of the German Bundestag.