Sun, Q, Chen, C, Kemp, AH et al. (1 more author) (2021) An on-board detection framework for polygon wear of railway wheel based on vibration acceleration of axle-box. Mechanical Systems and Signal Processing, 153. 107540. ISSN 0888-3270
Abstract
The polygon wear of railway wheel (PWRW) is a wear fault that is ubiquitous in railway vehicles. PWRW can induce a strong periodic excitation to both vehicle and track, which not only decreases passenger comfort but also is detrimental to the operational reliability and safety. Both the degree and the order of PWRW are important parameters used to quantify the fault. Because the fault-related components distribute at a wide range in the frequency domain, it is easy to alias with some radiated vibrations from vehicle and track components, which makes the on-board detection for both parameters of PWRW very difficult. To address the practical engineering problem, this paper proposes a detection framework based on the angle domain synchronous averaging technique (ADSAT). The detection method employs the vertical axle-box vibration acceleration (ABVA), which is easy to obtain and can also be used to monitor the conditions of axle-box bearings. The paper compares the proposed and traditional methods. The results reveal that the proposed method not only achieves the order detection which the traditional method cannot, but also mitigates the influence of background noise. The feasibility and effectiveness of the proposed method to improve the detection accuracy of PWRW is demonstrated through simulation and real field investigations.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020, Elsevier Ltd. All rights reserved. This is an author produced version of an article published in Mechanical Systems and Signal Processing. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Railway wheel polygonization; Rotating machine fault diagnosis; Angle domain synchronous averaging technique ; Axle-box vibration acceleration |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Jan 2021 16:51 |
Last Modified: | 19 Dec 2021 01:38 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.ymssp.2020.107540 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:170242 |