Bogie Speed Estimation and Signal Source Separation via Rail Vibration Analysis

G. Qin, Fengshou Gu, Yuandong Xu, Fulong Liu, Andrew Ball

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As an important part of high speed trains, any fault or failure of the bogie may cause fatal disaster and/or expensive lost. Considering on-train condition monitoring system is still restricted by many limits, bogie condition monitoring via rail vibration may be very valuable. For the rail vibration signals exited by bogies are short termed, non-periodic, non-stationary, not pre-separated corresponding to wheels, and with time-shifting of phases, they must be separated corresponding to each wheel for fault location. In this paper, to separate and reconstruct the vibration signals from two bogie wheels, a measurement mixing model is established and some assumptions about bogie speed, measure accordance, etc. are given. Based on envelope correlation analysis of signals from multi-sensors, the bogie speed and measurement windows are estimated so that the rail vibration signals can be separated corresponding to each bogie wheel, which allows the contact dynamics of the wheel-track to be characterized accurately for the purpose of diagnostics. A simulation and an experiment have been applied to verify this method. Some result as well as discussion will be given.
Original languageEnglish
Title of host publicationProceedings of COMADEM 2017
EditorsI. Sherrington, A. Onsy, R. Rao, H. Brooks, J. Philip
Pages200-208
Number of pages9
Publication statusPublished - Jul 2017
Event30th International Congress & Exhibition on Condition Monitoring and Diagnostic Engineering Management - University of Central Lancashire, Preston, United Kingdom
Duration: 10 Jul 201713 Jul 2017
Conference number: 30
http://www.comadem2017.com/ (Link to Conference Website)

Conference

Conference30th International Congress & Exhibition on Condition Monitoring and Diagnostic Engineering Management
Abbreviated titleCOMADEM 2017
CountryUnited Kingdom
CityPreston
Period10/07/1713/07/17
Internet address

Fingerprint

Source separation
Vibration analysis
Rails
Wheels
Condition monitoring
Electric fault location
Disasters
Sensors
Experiments

Cite this

Qin, G., Gu, F., Xu, Y., Liu, F., & Ball, A. (2017). Bogie Speed Estimation and Signal Source Separation via Rail Vibration Analysis. In I. Sherrington, A. Onsy, R. Rao, H. Brooks, & J. Philip (Eds.), Proceedings of COMADEM 2017 (pp. 200-208)
Qin, G. ; Gu, Fengshou ; Xu, Yuandong ; Liu, Fulong ; Ball, Andrew. / Bogie Speed Estimation and Signal Source Separation via Rail Vibration Analysis. Proceedings of COMADEM 2017. editor / I. Sherrington ; A. Onsy ; R. Rao ; H. Brooks ; J. Philip. 2017. pp. 200-208
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title = "Bogie Speed Estimation and Signal Source Separation via Rail Vibration Analysis",
abstract = "As an important part of high speed trains, any fault or failure of the bogie may cause fatal disaster and/or expensive lost. Considering on-train condition monitoring system is still restricted by many limits, bogie condition monitoring via rail vibration may be very valuable. For the rail vibration signals exited by bogies are short termed, non-periodic, non-stationary, not pre-separated corresponding to wheels, and with time-shifting of phases, they must be separated corresponding to each wheel for fault location. In this paper, to separate and reconstruct the vibration signals from two bogie wheels, a measurement mixing model is established and some assumptions about bogie speed, measure accordance, etc. are given. Based on envelope correlation analysis of signals from multi-sensors, the bogie speed and measurement windows are estimated so that the rail vibration signals can be separated corresponding to each bogie wheel, which allows the contact dynamics of the wheel-track to be characterized accurately for the purpose of diagnostics. A simulation and an experiment have been applied to verify this method. Some result as well as discussion will be given.",
keywords = "Signal source separation, Speed estimation, Rail vibration, Condition monitoring, Bogie",
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Qin, G, Gu, F, Xu, Y, Liu, F & Ball, A 2017, Bogie Speed Estimation and Signal Source Separation via Rail Vibration Analysis. in I Sherrington, A Onsy, R Rao, H Brooks & J Philip (eds), Proceedings of COMADEM 2017. pp. 200-208, 30th International Congress & Exhibition on Condition Monitoring and Diagnostic Engineering Management, Preston, United Kingdom, 10/07/17.

Bogie Speed Estimation and Signal Source Separation via Rail Vibration Analysis. / Qin, G.; Gu, Fengshou; Xu, Yuandong; Liu, Fulong; Ball, Andrew.

Proceedings of COMADEM 2017. ed. / I. Sherrington; A. Onsy; R. Rao; H. Brooks; J. Philip. 2017. p. 200-208.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - As an important part of high speed trains, any fault or failure of the bogie may cause fatal disaster and/or expensive lost. Considering on-train condition monitoring system is still restricted by many limits, bogie condition monitoring via rail vibration may be very valuable. For the rail vibration signals exited by bogies are short termed, non-periodic, non-stationary, not pre-separated corresponding to wheels, and with time-shifting of phases, they must be separated corresponding to each wheel for fault location. In this paper, to separate and reconstruct the vibration signals from two bogie wheels, a measurement mixing model is established and some assumptions about bogie speed, measure accordance, etc. are given. Based on envelope correlation analysis of signals from multi-sensors, the bogie speed and measurement windows are estimated so that the rail vibration signals can be separated corresponding to each bogie wheel, which allows the contact dynamics of the wheel-track to be characterized accurately for the purpose of diagnostics. A simulation and an experiment have been applied to verify this method. Some result as well as discussion will be given.

AB - As an important part of high speed trains, any fault or failure of the bogie may cause fatal disaster and/or expensive lost. Considering on-train condition monitoring system is still restricted by many limits, bogie condition monitoring via rail vibration may be very valuable. For the rail vibration signals exited by bogies are short termed, non-periodic, non-stationary, not pre-separated corresponding to wheels, and with time-shifting of phases, they must be separated corresponding to each wheel for fault location. In this paper, to separate and reconstruct the vibration signals from two bogie wheels, a measurement mixing model is established and some assumptions about bogie speed, measure accordance, etc. are given. Based on envelope correlation analysis of signals from multi-sensors, the bogie speed and measurement windows are estimated so that the rail vibration signals can be separated corresponding to each bogie wheel, which allows the contact dynamics of the wheel-track to be characterized accurately for the purpose of diagnostics. A simulation and an experiment have been applied to verify this method. Some result as well as discussion will be given.

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Qin G, Gu F, Xu Y, Liu F, Ball A. Bogie Speed Estimation and Signal Source Separation via Rail Vibration Analysis. In Sherrington I, Onsy A, Rao R, Brooks H, Philip J, editors, Proceedings of COMADEM 2017. 2017. p. 200-208