Search:
Computing and Library Services - delivering an inspiring information environment

The Validation of an ACS-SSI based Online Condition Monitoring for Railway Vehicle Suspension Systems using a SIMPACK Model

Liu, Fulong, Gu, Fengshou, Ball, Andrew, Zhao, Yunshi and Peng, Bo (2017) The Validation of an ACS-SSI based Online Condition Monitoring for Railway Vehicle Suspension Systems using a SIMPACK Model. Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017).

[img]
Preview
PDF - Accepted Version
Download (865kB) | Preview

Abstract

To enhance the safe operation of modern railway vehicles, an online condition monitoring scheme is proposed for vehicle suspension systems. The core technology of the scheme is based on the average correlation signals based stochastic subspace identification (ACS-SSI) algorithm which allows system identification to be implemented reliably with output signals only that have strong noise and nonlinearity in vehicle applications. To validate the scheme, a series simulation studies were carried out based on a more realistic bogie model, developed in SIMPACK, under typical random excitations including vertical, lateral, rolling and gauging directions. ACS-SSI then applied to the signals from the model under common faults in the bogie suspensions to identify the system parameters. The agreeable results obtained by comparing the identified results with that calculated by SIMPACK shows that the proposed scheme performs reliably in obtaining the system parameters: modal frequency, damping and shape that are required for online diagnosis.

Item Type: Article
Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: Railway vehicle suspension; Online condition monitoring; ACS-SSI
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Schools: School of Computing and Engineering
Related URLs:
Depositing User: Jonathan Cook
Date Deposited: 09 Oct 2017 10:08
Last Modified: 11 Dec 2017 19:29
URI: http://eprints.hud.ac.uk/id/eprint/33644

Downloads

Downloads per month over past year

Repository Staff Only: item control page

View Item View Item

University of Huddersfield, Queensgate, Huddersfield, HD1 3DH Copyright and Disclaimer All rights reserved ©