A novel refined dynamic model of high-speed maglev train-bridge coupled system for random vibration and running safety assessment

Abstract

Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern, especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations. A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper, in which multi-source uncertainty excitation can be considered simultaneously, and the probability density evolution method (PDEM) is adopted to reveal the system-specific uncertainty dynamic characteristic. The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle, and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges, which are directly established by using finite element method. The model is proven to be applicable by comparing with Monte Carlo simulation. By applying the proposed stochastic framework to the high maglev line, the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment. Moreover, the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated. The results show that the augmentation of train speed will move backward the sensitive wavelength interval, and track irregularity amplitude influences the response remarkably in the sensitive interval.

Keywords

maglev train-bridge interaction / electromagnetic force-air gap model / stochastic dynamic analysis / running safety assessment / probability density evolution method

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