Onboard detection of railway axle bearing defects using envelope analysis of high frequency acoustic emission signals. (November 2016)

• Record Type: Journal Article
• Authors: Amini, Arash; Entezami, Mani; Papaelias, Mayorkinos
• Is Part Of: Case studies in nondestructive testing and evaluation. Volume 6: Part A(2016:Oct.)
• Page Start: 8
• Page End: 16
• Publication Date: 2016-11
• Subjects: Nondestructive testing -- Case studies -- Periodicals; Electronic journals; 620.112705
• DOI: 10.1016/j.csndt.2016.06.002
• Languages: English
• ISSNs: 2214-6571

Abstract

Abstract: Railway wheelsets consist of three main components; the wheel, axle and axle bearing. Faults can develop on any of the aforementioned components, but the most common are related to wheel and axle bearing damages. The continuous increase in train operating speeds means that failure of an axle bearing can lead to very serious derailments, potentially causing human casualties, severe disruption in the operation of the network, damage to the tracks, unnecessary costs, and loss of confidence in rail transport by the general public. The rail industry has focused on the improvement of maintenance and online condition monitoring of rolling stock to reduce the probability of failure as much as possible. This paper discusses the results of onboard acoustic emission measurements carried out on freight wagons with artificially damaged axle bearings in Long Marston, UK. Acoustic emission signal envelope analysis has been applied as a means of effective tool to detect and evaluate the damage in the bearings considered in this study. From the results obtained it is safe to conclude that acoustic emission signal envelope analysis has the capability of detecting and evaluating faulty axle bearings along with their characteristic defect frequencies in the real-world conditions. Highlights: The use of high-frequency acoustic emission for train axle bearing fault detection. Onboard monitoring of railway axle bearings. Application of envelope analysis for filtering the signal from random noise sources. Field experiment and data analysis results. The use of acoustic emission in monitoring rolling stock axle bearings has never been attempted previously..