Multivariate error assessment of response time histories method for dynamic systems  

作　　者：Zhen-fei ZHAN Jie HU Yan FU Ren-Jye YANG Ying-hong PENG Jin QI 

机构地区：[1]School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China [2]Research and Innovation Center,Ford Motor Company,Dearborn,M148124,USA

出　　处：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2012年第2期121-131,共11页浙江大学学报（英文版）A辑（应用物理与工程）

基　　金：supported by the National Natural Science Fundation of China (No. 51075262);the New Century Excellent Talents in University Program (No. NCET-08-0361);the Fund for the Doctoral Program of Higher Education (No. 200802480036), China

摘　　要：In this paper, an integrated validation method and process are developed for multivariate dynamic systems. The principal component analysis approach is used to address multivariate correlation and dimensionality reduction, the dynamic time warping and correlation coefficient are used for error assessment, and the subject matter experts (SMEs)’ opinions and principal component analysis coefficients are incorporated to provide the overall rating of the dynamic system. The proposed method and process are successfully demonstrated through a vehicle dynamic system problem.In this paper, an integrated validation method and process are developed for multivariate dynamic systems. The principal component analysis approach is used to address multivariate correlation and dimensionality reduction, the dynamic time warping and correlation coefficient are used for error assessment, and the subject matter experts （SMEs）＇ opinions and principal component analysis coefficients are incorporated to provide the overall rating of the dynamic system. The proposed method and process are successfully demonstrated through a vehicle dynamic system problem.

关 键 词：Model validation Multivariate dynamic resnonses. Princioal component analvsis. Dvnamic time warping 

分 类 号：TP391.72[自动化与计算机技术—计算机应用技术]