Title :
Rail vehicle ride comfort prediction based on bogie acceleration measurements
Author :
Xiukun Wei ; Yan Liu ; Qu Sun ; Limin Jia ; Yuting Wang
Author_Institution :
State Key Lab. of Rail Traffic Control & Safety, Beijing Jiaotong Univ., Beijing, China
Abstract :
Ride comfort is one of the most significant dynamic performance characteristics of railway vehicles. It is imperative to monitor and predict the vehicle ride comfort online especially for modern rail vehicles. In this paper, an innovative online rail vehicle ride comfort prediction method is proposed. By using the acceleration measurements from the sensors equipped on the bogies, the dynamical acceleration of the carbody is estimated by using principle component analysis (PCA) and partial least square (PLS) techniques. The ride comfort is further calculated by using the estimated three way acceleration signals. The proposed method is validated by using the professional rail vehicle simulation software, SIMPACK.
Keywords :
acceleration measurement; least squares approximations; principal component analysis; railway rolling stock; sensors; PCA; PLS technique; SIMPACK; bogie acceleration measurement; carbody; dynamic performance characteristics; dynamical acceleration; innovative online rail vehicle ride comfort prediction method; partial least square technique; principle component analysis; professional rail vehicle simulation software; rail vehicle ride comfort prediction; sensors; vehicle ride comfort online monitoring; Acceleration; Mathematical model; Predictive models; Principal component analysis; Rails; Vehicles; Vibrations; Acceleration and Band-pass filter; Partial least square; Ride comfort;
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
DOI :
10.1109/CCDC.2013.6561613
