Identification of Behavioural Models for Railway Turnouts Monitoring
Abstract
This study introduces a low-complexity behavioural model to describe the dynamic response of railway turnouts due to the ballast and railpad components. The behavioural model should serve as the basis for the future development of a supervisory system for the continuous monitoring of turnouts. A fourth order linear model is proposed based on spectral analysis of measured rail vertical accelerations gathered during a receptance test and it is then identified at several sections of the turnout applying the Eigensystem Realization Algorithm. The predictviness and robustness of the behavioural models have been assessed on a large data set of train passages differing for train type, speed and loading condition. Last, the need for a novel modeling method is argued in relation to high-fidelity mechanistic models widely used in the railway engineering community.
Keywords
Cite
@article{arxiv.1910.06582,
title = {Identification of Behavioural Models for Railway Turnouts Monitoring},
author = {Pegah Barkhordari and Roberto Galeazzi and Alejandro de Miguel Tejada and Ilmar F. Santos},
journal= {arXiv preprint arXiv:1910.06582},
year = {2019}
}
Comments
26 pages, 15 figures, submitted for evaluation to Elsevier journal