Online condition monitoring of rolling stock wheels and axle bearings. (March 2016)

• Record Type: Journal Article
• Authors: Papaelias, Mayorkinos; Amini, Arash; Huang, Zheng; Vallely, Patrick; Dias, Daniel Cardoso; Kerkyras, Spyridon
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 230:Number 3(2016)
• Page Start: 709
• Page End: 723
• Publication Date: 2016-03
• Subjects: Railway -- train -- axle bearing -- onboard -- fault detection -- acoustic emission -- vibration -- signal analysis; Railroads -- Periodicals; Personal rapid transit -- Periodicals; 625.1
• DOI: 10.1177/0954409714559758
• Languages: English
• ISSNs: 0954-4097

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.