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Foil bearing is considered to be a promising supporting technology in high-speed centrifugal machinery. Due to the high-speed shearing effect in the viscous lubricant film, heat generation could not be ignored. In this paper, a thermo-elastic model of the multi-leaf foil thrust bearing is proposed to predict its thermal and static characteristics. In the model, modified Reynolds equation, energy equation, and Kirchhoff equation are solved in a coupling way. The contact area between the foil and welding plate is taken into account. Besides, the effect of cooling air on the bearing temperature is investigated. The ultimate load capacity and transient overload failure process of the bearing is analyzed and discussed. The effect of rotation speed on the bearing temperature is more obvious than that of the bearing load. The bearing temperature drops obviously by introducing the cooling air, and the cooling effect is improved with the supply pressure. The transient overload failure of the bearing occurs when the bearing load exceeds the ultimate value.

Due to harsh working conditions and complicated external load, fatigue crack and fracture failure of the vibroseis baseplate usually occur during load cycles. To improve the fatigue resistance and extend the service life of the baseplates, this article studies the fatigue behavior of the baseplate materials and analyzes its fatigue reliability using fracture mechanics. Initially, the baseplate fatigue life is predicted by the crack propagation model based on the Paris' and Forman's laws. Three welded characteristic specimens of the baseplate are designed and fatigue is tested under a three-point bending load. The strain value and the crack propagation loading cycles are recorded during the test. Meanwhile, the crack propagation, damage, and fracture region of all the specimens are observed and tracked by scanning electron microscopy, which determines the fatigue damage mechanism of the baseplate. The fatigue reliability and parameter sensitivity analysis have been the subjects of previous research due to the randomness of the fatigue parameters. Finally, the most important random parameters are optimized based on the reliability analysis. As a result, the fatigue life reaches its maximum, and the reliability increases by 1.8%, resulting in a significant improvement in the fatigue resistance ability.