contributor author | Ling Ye | |
contributor author | Hua-Peng Chen | |
contributor author | Sheng-Nan Wang | |
date accessioned | 2022-02-01T00:24:40Z | |
date available | 2022-02-01T00:24:40Z | |
date issued | 5/1/2021 | |
identifier other | %28ASCE%29AS.1943-5525.0001259.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4271392 | |
description abstract | Real-time identification and monitoring of the railway track dynamic parameters are necessary to ensure the safe operation of the railway transportation systems. Traditional global structural parameter identification methods have the problem of low efficiency in identifying structural parameters of railway track dynamic systems. To tackle the inefficiency problem, this paper proposes a new parameter identification method for railway track systems on the basis of the substructural identification algorithm. First, the railway track system is divided into several substructures depending on the vehicle loads. The parametric expression of the interface forces of the target substructure is constructed by the Chebyshev polynomials. Then, the sensitivity of the dynamic responses to the structural parameters and the interface force parameters can be obtained. The substructure parameters and the load parameters are identified simultaneously by the coupled iterative optimization algorithm based on the sensitivity analysis. The proposed substructural identification method greatly improves computational efficiency in the iterative process of parameter identification because the proposed method significantly reduces the number of parameters to be identified. Finally, a numerical example for a railway track dynamic system is employed to demonstrate the effectiveness of the proposed substructural identification method. The results from the numerical study show that changes in the structural parameters of rail track systems can be accurately identified using the proposed substructural identification method. | |
publisher | ASCE | |
title | Substructural Identification Methods for Parameter Estimation of Railway Track Dynamic Systems | |
type | Journal Paper | |
journal volume | 34 | |
journal issue | 3 | |
journal title | Journal of Aerospace Engineering | |
identifier doi | 10.1061/(ASCE)AS.1943-5525.0001259 | |
journal fristpage | 04021014-1 | |
journal lastpage | 04021014-12 | |
page | 12 | |
tree | Journal of Aerospace Engineering:;2021:;Volume ( 034 ):;issue: 003 | |
contenttype | Fulltext | |