期刊
VEHICLE SYSTEM DYNAMICS
卷 55, 期 3, 页码 427-448出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00423114.2016.1270456
关键词
Vehicle-track coupled system; stochastic analysis; track random irregularity; random system parameters; probability density evolution method
资金
- Scientific and Technological Research and Development Project of China Railway Corporation [2014G001-G]
- National Basic Research Program of China (973 Program) [2013CB036206, 2013CB036205]
- Fundamental Research Funds for the Central Universities [2682015CX045]
- National Natural Science Fund [51478482, 51678507]
- Program of Intelligence Introduction for Innovation in Rail Transit Engineering [B16041]
- Opening Foundation of State Key Laboratory of Traction Power, Southwest Jiaotong University [TPL1604]
The vehicle-track coupled system has a random nature in the time-space domain. This paper proposes a computational model to analyse the temporal-spatial stochastic vibrations of vehicle-track systems, where the vehicle-track system is divided into a vehicle subsystem, track subsystem, and interfacial subsystem between the wheel and rail. In this model, the time-varying randomicity of dynamical parameters of the vehicle system, correlation, and randomness of the track structural parameters in the time-space joint dimensions, and randomness of the track random irregularities are considered. A probability dimension-reduction method was used to randomly combine different random variables. Furthermore, the probability density evolution method was applied to solve the delivery problem of probabilities between excitation inputs and response outputs. The temporal-spatial stochastic vibrations of the vehicle-track system with different coefficients of variation were studied, in which we assumed that the dynamic parameters obeyed the normal distribution, and the stochastic simulation method of the track random irregularities is probed into. The calculated results from this model are consistent with the actual measured results and physical conceptions. Thus, the temporal-spatial stochastic evolutionary mechanism can be explored, and the limits of dynamic indices can be formulated by using this developed model.
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