Wheel-rail profile condition monitoring

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Authors

Colleges, School and Institutes

External organisations

  • Loughborough University

Abstract

Increased railway patronage worldwide is putting pressure on rolling stock and infrastructure to operate at higher capacity and with improved punctuality. Condition monitoring is seen as a contributing factor in enabling this and is highlighted here in the context of rolling stock being procured with high capacity data buses, multiple sensors and centralised control. This therefore leaves scope for advanced computational diagnostic concepts. The rail vehicle bogie and associated wheelsets are one of the largest and most costly areas of maintenance on rolling stock and presented here is a potential method for real time estimation of wheel-rail contact wear to move this currently scheduled based assessment to condition based assessment. This technique utilises recursive 'grey box' least squares system identification, used in a piecewise linear manner, to capture the strongly discontinuous nonlinear nature of the wheel-rail geometry.

Details

Original languageEnglish
Title of host publicationUKACC International Conference on CONTROL 2010
Publication statusPublished - 1 Dec 2010
EventUKACC International Conference on CONTROL 2010 - Coventry, United Kingdom
Duration: 7 Sep 201010 Sep 2010

Conference

ConferenceUKACC International Conference on CONTROL 2010
CountryUnited Kingdom
CityCoventry
Period7/09/1010/09/10

Keywords

  • Accelerometers, Fault diagnosis/detection, Kalman filters, Nonlinear systems, Piecewise linear analysis, Railways, Recursive least squares, Vehicle dynamics

ASJC Scopus subject areas