Random Response Analysis of Axle-Box Bearing of a High-Speed Train Excited by Crosswinds and Track Irregularities

The Axle-box bearing (ABB) is a key component in the high-speed train which suffers multiple stochastic excitations in realistic working conditions. The ABB's health status is crucial for the reliable and safe operation of the rolling stock. This paper proposes a novel stochastic vehicle–track coupled model to evaluate the dynamic performance of ABBs in a high-speed train with unsteady wind load and random track irregularities. The nonlinear bearing stiffness and unsmooth nonlinearities of the bearing clearances are properly considered based on the Hertzian contact theory. The von Karman power spectral density is adopted to generate the time-history of the fluctuating wind speed on a moving vehicle. The unsteady wind loads acting on the carbody are derived based on the fluid-induced vibration theory. The empirical PSD of track irregularity is adopted to generate the time-history of track irregularities. The Monte Carlo method is employed to analyse the roller–raceway contact stress with random excitations of unsteady wind and track irregularities. The results indicate that the crosswind causes the partial loading phenomenon of the ABBs. The increase of crosswind speed significantly increases the probability of the contact stress exceeding the safety threshold, which challenges the service safety of the key components inside the train.