ABSTRACT
ABSTRACT: There is a great interest to predict the long-time evolution of the track irregularities for a given track portion of the high-speed train network, in order to be able to anticipate the start off of the maintenance operations. In this paper, a stochastic predictive model is proposed for predicting the long-time evolution of a vector-valued random dynamic indicator related to the nonlinear dynamic responses of the high-speed train excited by the stochastic track irregularities. The long-time evolution of the vector-valued random indicator is modeled by a discrete nonGaussian nonstationary stochastic model (ARMA type model), for which the coefficients are time-dependent. The quality assessment of the stochastic predictive model is presented, which validates the proposed stochastic model.
