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Online condition monitoring of railway wheelsets

Amini, Arash (2016)
Ph.D. thesis, University of Birmingham.

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Abstract

The rail industry has focused on the improvement of maintenance through the effective use of online condition monitoring of rolling stock and rail infrastructure in order to reduce the occurrence of unexpected catastrophic failures and disruption that arises from them to an absolute minimum. The basic components comprising a railway wheelset are the wheels, axle and axle bearings. Detection of wheelset faults in a timely manner increases efficiency as it helps minimise maintenance costs and increase availability. The main aim of this project has been the development of a novel integrated online acoustic emission (AE) and vibration testing technique for the detection of wheel and axle bearing defects as early as possible and well before they result in catastrophic failure and subsequently derailment. The approach employed within this research study has been based on the combined use of accelerometers and high-frequency acoustic emission sensors mounted on the rail or axle box using magnetic hold-downs. Within the framework of this project several experiments have been carried out under laboratory conditions, as well as in the field at the Long Marston Test Track and in Cropredy on the Chiltern Railway line to London.

Type of Work:Ph.D. thesis.
Supervisor(s):Papaelias, Mayorkinos and Roberts, Clive
School/Faculty:Colleges (2008 onwards) > College of Engineering & Physical Sciences
Department:School of Electronic, Electrical and System Engineering
Additional Information:

A. Amini, M. Entezami, M. Papaelias “Onboard detection of railway axle bearing defects using envelope analysis of high frequency acoustic emission signals”. Journal of Case Studies in Non-destructive Testing and Evaluation,vol 6, p 8-16 June 2016.http://dx.doi.org/10.1016/j.csndt.2016.06.002
M. Papaelias, A. Amini, Z. Huang, P. Vallely, D. Cardoso Dias, S. Kerkyras “Online condition monitoring of rolling stock and axle bearings”. Proceedings of IMechE-Part F: Journal of Rail and Rapid Transit vol. 230 no. 3, p 709-723 March 2016. http://dx.doi/org/10.1177/0954409714559758

Subjects:QA76 Computer software
TF Railroad engineering and operation
Institution:University of Birmingham
ID Code:6957
This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder.
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