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Online condition monitoring of rolling stock wheels and axle bearings.

Authors :
Papaelias, Mayorkinos
Amini, Arash
Huang, Zheng
Vallely, Patrick
Dias, Daniel Cardoso
Kerkyras, Spyridon
Source :
Proceedings of the Institution of Mechanical Engineers -- Part F -- Journal of Rail & Rapid Transit (Sage Publications, Ltd.); Mar2016, Vol. 230 Issue 3, p709-723, 15p
Publication Year :
2016

Abstract

The early detection of faults in rolling stock wheels and axle bearings is of paramount importance for rail infrastructure managers as it contributes to the safety of rail operations. In this paper we report on the key results that have arisen from the development and implementation of a novel condition monitoring system based on high-frequency acoustic emission and vibration analysis installed on a train. The novel system makes use of inexpensive and robust acoustic emission sensors and accelerometers, which can be easily installed on the axle bearing box with minimal intervention required. Experimental work carried out under actual conditions at the Long Marston rail track and on the Lisbon – Cas-Cais suburban line has proven that the developed system is capable of detecting wheel and axle bearing-related defects with various levels of severity. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09544097
Volume :
230
Issue :
3
Database :
Complementary Index
Journal :
Proceedings of the Institution of Mechanical Engineers -- Part F -- Journal of Rail & Rapid Transit (Sage Publications, Ltd.)
Publication Type :
Academic Journal
Accession number :
113263884
Full Text :
https://doi.org/10.1177/0954409714559758