Random vibration analysis of the maglev vehicle-guideway system using a probability density evolution method with uncertain parameters

Abstract

Random dynamic analyses of maglev vehicle-guideway coupled systems are of significant interest but have yet been comprehensively performed. This paper presents a time-dependent coupled random model of a maglev vehicle-controller-guideway-pier to investigate random vibration characteristics of the dynamic system. In the study, a 12-degree-of-freedom vehicle model is considered, a three-dimensional detailed guideway model is established using the finite element method, and the electromagnetic levitation force is controlled with a current feedback controller. Then, the generalized F-discrepancy representative point set selection strategy and probability density evolution method, which can consider multiple random parameters, are combined to analyze the dynamic system. Random vehicle parameters and irregularity are introduced and the mean value, standard deviation, limits satisfying different probability guarantee rates, and probabilistic information are calculated. The model was validated with field measurement data from an electromagnetic suspension (EMS) maglev line. In addition, the Monte Carlo method was used to assess the accuracy and efficiency of the proposed method. The results demonstrate that the proposed method has good accuracy and efficiency. The effects of vehicle running speed, random irregularity, and random vehicle loads on the dynamic vibration of the system are discussed.