Vibration-Based Detection of Wheel Flat on a High-Speed Train

Ruichen Wang; David Crosbee; Adam Bevan; Zhiwei Wang; Dong Zhen

doi:10.1007/978-3-030-57745-2_14

Vibration-Based Detection of Wheel Flat on a High-Speed Train

Ruichen Wang, David Crosbee, Adam Bevan, Zhiwei Wang, Dong Zhen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

Wheel flat is not only commonly unavoidable surface damage in railway wheels, it can result in possible damage and deterioration incurring high risk of running safety and high maintenance costs. Wheel flat is therefore necessary to be detected at an early stage to minimise safety hazard and maintenance work. This study explores the capacity of the vibration-based detection for high-speed train wheel flatness. A more realistic vehicle-track coupling dynamic model (a dynamic model of vehicle systems of 94 degrees of freedom with wheel flat) considering the dynamic factors of traction transmission, gear transmission and the track geometry irregularities, is established to calculate the dynamic responses of axlebox. In this paper, the proposed method is focus on processing the axle box vertical vibration caused by wheel flat in conventional time and frequency domain, as well as the envelope analysis with a band pass filter. Results demonstrate that the wheel flat can be successfully detected in a more realistic vehicle model, provide an efficient way to the wheel flat detection.

Original language	English
Title of host publication	Advances in Asset Management and Condition Monitoring
Subtitle of host publication	COMADEM 2019
Editors	Andrew Ball, Len Gelman, B. K. N. Rao
Publisher	Springer
Pages	159-169
Number of pages	11
Volume	166
ISBN (Electronic)	9783030577452
ISBN (Print)	9783030577445
DOIs	https://doi.org/10.1007/978-3-030-57745-2_14
Publication status	Published - 28 Aug 2020
Event	32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference - University of Huddersfield, Huddersfield, United Kingdom Duration: 3 Sep 2019 → 5 Sep 2019 Conference number: 32 http://www.comadem2019.com/ (Link to Conference Website)

Publication series

Name	Smart Innovation, Systems and Technologies
Publisher	Springer
Volume	166
ISSN (Print)	2190-3018
ISSN (Electronic)	2190-3026

Conference

Conference	32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference
Abbreviated title	COMADEM 2019
Country/Territory	United Kingdom
City	Huddersfield
Period	3/09/19 → 5/09/19
Internet address	http://www.comadem2019.com/ (Link to Conference Website)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-030-57745-2_14Licence: Unspecified

Cite this

Wang, R., Crosbee, D., Bevan, A., Wang, Z., & Zhen, D. (2020). Vibration-Based Detection of Wheel Flat on a High-Speed Train. In A. Ball, L. Gelman, & B. K. N. Rao (Eds.), Advances in Asset Management and Condition Monitoring: COMADEM 2019 (Vol. 166, pp. 159-169). (Smart Innovation, Systems and Technologies; Vol. 166). Springer. https://doi.org/10.1007/978-3-030-57745-2_14

@inproceedings{6153d64d42cf435a8159165d66dc8fe5,

title = "Vibration-Based Detection of Wheel Flat on a High-Speed Train",

abstract = "Wheel flat is not only commonly unavoidable surface damage in railway wheels, it can result in possible damage and deterioration incurring high risk of running safety and high maintenance costs. Wheel flat is therefore necessary to be detected at an early stage to minimise safety hazard and maintenance work. This study explores the capacity of the vibration-based detection for high-speed train wheel flatness. A more realistic vehicle-track coupling dynamic model (a dynamic model of vehicle systems of 94 degrees of freedom with wheel flat) considering the dynamic factors of traction transmission, gear transmission and the track geometry irregularities, is established to calculate the dynamic responses of axlebox. In this paper, the proposed method is focus on processing the axle box vertical vibration caused by wheel flat in conventional time and frequency domain, as well as the envelope analysis with a band pass filter. Results demonstrate that the wheel flat can be successfully detected in a more realistic vehicle model, provide an efficient way to the wheel flat detection.",

keywords = "Wheel flat, axle box, high-speed train, vibration-based detection, Vibration-based detection, High-speed train, Axle box",

author = "Ruichen Wang and David Crosbee and Adam Bevan and Zhiwei Wang and Dong Zhen",

year = "2020",

month = aug,

day = "28",

doi = "10.1007/978-3-030-57745-2_14",

language = "English",

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volume = "166",

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editor = "Andrew Ball and Len Gelman and Rao, {B. K. N. }",

booktitle = "Advances in Asset Management and Condition Monitoring",

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note = "32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference, COMADEM 2019 ; Conference date: 03-09-2019 Through 05-09-2019",

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Wang, R, Crosbee, D , Bevan, A, Wang, Z & Zhen, D 2020, Vibration-Based Detection of Wheel Flat on a High-Speed Train. in A Ball, L Gelman & BKN Rao (eds), Advances in Asset Management and Condition Monitoring: COMADEM 2019. vol. 166, Smart Innovation, Systems and Technologies, vol. 166, Springer, pp. 159-169, 32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference, Huddersfield, United Kingdom, 3/09/19. https://doi.org/10.1007/978-3-030-57745-2_14

Vibration-Based Detection of Wheel Flat on a High-Speed Train. / Wang, Ruichen; Crosbee, David ; Bevan, Adam et al.

Advances in Asset Management and Condition Monitoring: COMADEM 2019. ed. / Andrew Ball; Len Gelman; B. K. N. Rao. Vol. 166 Springer, 2020. p. 159-169 (Smart Innovation, Systems and Technologies; Vol. 166).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Vibration-Based Detection of Wheel Flat on a High-Speed Train

AU - Wang, Ruichen

AU - Crosbee, David

AU - Bevan, Adam

AU - Wang, Zhiwei

AU - Zhen, Dong

N1 - Conference code: 32

PY - 2020/8/28

Y1 - 2020/8/28

N2 - Wheel flat is not only commonly unavoidable surface damage in railway wheels, it can result in possible damage and deterioration incurring high risk of running safety and high maintenance costs. Wheel flat is therefore necessary to be detected at an early stage to minimise safety hazard and maintenance work. This study explores the capacity of the vibration-based detection for high-speed train wheel flatness. A more realistic vehicle-track coupling dynamic model (a dynamic model of vehicle systems of 94 degrees of freedom with wheel flat) considering the dynamic factors of traction transmission, gear transmission and the track geometry irregularities, is established to calculate the dynamic responses of axlebox. In this paper, the proposed method is focus on processing the axle box vertical vibration caused by wheel flat in conventional time and frequency domain, as well as the envelope analysis with a band pass filter. Results demonstrate that the wheel flat can be successfully detected in a more realistic vehicle model, provide an efficient way to the wheel flat detection.

AB - Wheel flat is not only commonly unavoidable surface damage in railway wheels, it can result in possible damage and deterioration incurring high risk of running safety and high maintenance costs. Wheel flat is therefore necessary to be detected at an early stage to minimise safety hazard and maintenance work. This study explores the capacity of the vibration-based detection for high-speed train wheel flatness. A more realistic vehicle-track coupling dynamic model (a dynamic model of vehicle systems of 94 degrees of freedom with wheel flat) considering the dynamic factors of traction transmission, gear transmission and the track geometry irregularities, is established to calculate the dynamic responses of axlebox. In this paper, the proposed method is focus on processing the axle box vertical vibration caused by wheel flat in conventional time and frequency domain, as well as the envelope analysis with a band pass filter. Results demonstrate that the wheel flat can be successfully detected in a more realistic vehicle model, provide an efficient way to the wheel flat detection.

KW - Wheel flat

KW - axle box

KW - high-speed train

KW - vibration-based detection

KW - Vibration-based detection

KW - High-speed train

KW - Axle box

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T3 - Smart Innovation, Systems and Technologies

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BT - Advances in Asset Management and Condition Monitoring

A2 - Ball, Andrew

A2 - Gelman, Len

A2 - Rao, B. K. N.

PB - Springer

T2 - 32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference

Y2 - 3 September 2019 through 5 September 2019

ER -

Vibration-Based Detection of Wheel Flat on a High-Speed Train

Abstract

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UN SDGs

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