Wheel-rail profile condition monitoring
Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language | English |
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Title of host publication | UKACC International Conference on CONTROL 2010 |
Publication status | Published - 1 Dec 2010 |
Event | UKACC International Conference on CONTROL 2010 - Coventry, United Kingdom Duration: 7 Sep 2010 → 10 Sep 2010 |
Conference
Conference | UKACC International Conference on CONTROL 2010 |
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Country | United Kingdom |
City | Coventry |
Period | 7/09/10 → 10/09/10 |
Keywords
- Accelerometers, Fault diagnosis/detection, Kalman filters, Nonlinear systems, Piecewise linear analysis, Railways, Recursive least squares, Vehicle dynamics