Estimation of railway vehicle suspension parameters for condition monitoring

Ping Li, Roger Goodall, Paul Weston, Chung Seng Ling, Colin Goodman, Clive Roberts

Research output: Contribution to journalArticle

132 Citations (Scopus)

Abstract

This paper investigates the problem of parameter estimation for railway vehicle suspensions so as to provide information to support condition-based (instead of calendar-based) maintenance. A simplified plan view railway vehicle dynamical model is derived and a newly developed Rao-Blackwellized particle filter (RBPF) based method is used for parameter estimation. Computer simulations are carried out to assess and compare the performance of parameter estimation with different sensor configurations as well as the robustness with respect to the uncertainty in the statistics of the random track inputs. The method is then verified practically using real test data from a Coradia Class 175 railway vehicle with only bogie and body mounted sensors, and some preliminary results are presented.

Original languageEnglish
Pages (from-to)43-55
Number of pages13
JournalControl Engineering Practice
Volume15
Issue number1
Early online date17 Apr 2006
DOIs
Publication statusPublished - Jan 2007
Externally publishedYes

Fingerprint

Vehicle suspensions
Condition Monitoring
Condition monitoring
Railway
Parameter estimation
Parameter Estimation
Sensor
Calendar
Sensors
Particle Filter
Dynamical Model
Maintenance
Computer Simulation
Statistics
Robustness
Uncertainty
Configuration
Computer simulation

Cite this

Li, Ping ; Goodall, Roger ; Weston, Paul ; Seng Ling, Chung ; Goodman, Colin ; Roberts, Clive. / Estimation of railway vehicle suspension parameters for condition monitoring. In: Control Engineering Practice. 2007 ; Vol. 15, No. 1. pp. 43-55.
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Estimation of railway vehicle suspension parameters for condition monitoring. / Li, Ping; Goodall, Roger; Weston, Paul; Seng Ling, Chung; Goodman, Colin; Roberts, Clive.

In: Control Engineering Practice, Vol. 15, No. 1, 01.2007, p. 43-55.

Research output: Contribution to journalArticle

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