The Validation of an ACS-SSI based Online Condition Monitoring for Railway Vehicle Suspension Systems using a SIMPACK Model

Fulong Liu, Fengshou Gu, Andrew Ball, Yunshi Zhao, Bo Peng

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

2 Citations (Scopus)

Abstract

To enhance the safe operation of modern railway vehicles, an online condition monitoring scheme is proposed for vehicle suspension systems. The core technology of the scheme is based on the average correlation signals based stochastic subspace identification (ACS-SSI) algorithm which allows system identification to be implemented reliably with output signals only that have strong noise and nonlinearity in vehicle applications. To validate the scheme, a series simulation studies were carried out based on a more realistic bogie model, developed in SIMPACK, under typical random excitations including vertical, lateral, rolling and gauging directions. ACS-SSI then applied to the signals from the model under common faults in the bogie suspensions to identify the system parameters. The agreeable results obtained by comparing the identified results with that calculated by SIMPACK shows that the proposed scheme performs reliably in obtaining the system parameters: modal frequency, damping and shape that are required for online diagnosis.
Original languageEnglish
Title of host publicationProceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9780701702601
ISBN (Print)9781509050406
DOIs
Publication statusPublished - 26 Oct 2017
Event23rd International Conference on Automation and Computing: Addressing Global Challenges through Automation and Computing - University of Huddersfield, Huddersfield, United Kingdom
Duration: 7 Sep 20178 Sep 2017
Conference number: 23
https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042 (Link to Conference Website)

Conference

Conference23rd International Conference on Automation and Computing
Abbreviated titleICAC 2017
CountryUnited Kingdom
CityHuddersfield
Period7/09/178/09/17
OtherThe scope of the conference covers a broad spectrum of areas with multi-disciplinary interests in the fields of automation, control engineering, computing and information systems, ranging from fundamental research to real-world applications.
Internet address

Fingerprint

Vehicle suspensions
Condition monitoring
Identification (control systems)
Gaging
Damping

Cite this

Liu, F., Gu, F., Ball, A., Zhao, Y., & Peng, B. (2017). The Validation of an ACS-SSI based Online Condition Monitoring for Railway Vehicle Suspension Systems using a SIMPACK Model. In Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017) Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/IConAC.2017.8082030
Liu, Fulong ; Gu, Fengshou ; Ball, Andrew ; Zhao, Yunshi ; Peng, Bo. / The Validation of an ACS-SSI based Online Condition Monitoring for Railway Vehicle Suspension Systems using a SIMPACK Model. Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017). Institute of Electrical and Electronics Engineers Inc., 2017.
@inproceedings{6c4eba9de03843548c38159824c7521c,
title = "The Validation of an ACS-SSI based Online Condition Monitoring for Railway Vehicle Suspension Systems using a SIMPACK Model",
abstract = "To enhance the safe operation of modern railway vehicles, an online condition monitoring scheme is proposed for vehicle suspension systems. The core technology of the scheme is based on the average correlation signals based stochastic subspace identification (ACS-SSI) algorithm which allows system identification to be implemented reliably with output signals only that have strong noise and nonlinearity in vehicle applications. To validate the scheme, a series simulation studies were carried out based on a more realistic bogie model, developed in SIMPACK, under typical random excitations including vertical, lateral, rolling and gauging directions. ACS-SSI then applied to the signals from the model under common faults in the bogie suspensions to identify the system parameters. The agreeable results obtained by comparing the identified results with that calculated by SIMPACK shows that the proposed scheme performs reliably in obtaining the system parameters: modal frequency, damping and shape that are required for online diagnosis.",
keywords = "Railway vehicle suspension, Online condition monitoring, ACS-SSI",
author = "Fulong Liu and Fengshou Gu and Andrew Ball and Yunshi Zhao and Bo Peng",
year = "2017",
month = "10",
day = "26",
doi = "10.23919/IConAC.2017.8082030",
language = "English",
isbn = "9781509050406",
booktitle = "Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

Liu, F, Gu, F, Ball, A, Zhao, Y & Peng, B 2017, The Validation of an ACS-SSI based Online Condition Monitoring for Railway Vehicle Suspension Systems using a SIMPACK Model. in Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017). Institute of Electrical and Electronics Engineers Inc., 23rd International Conference on Automation and Computing, Huddersfield, United Kingdom, 7/09/17. https://doi.org/10.23919/IConAC.2017.8082030

The Validation of an ACS-SSI based Online Condition Monitoring for Railway Vehicle Suspension Systems using a SIMPACK Model. / Liu, Fulong; Gu, Fengshou; Ball, Andrew; Zhao, Yunshi; Peng, Bo.

Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017). Institute of Electrical and Electronics Engineers Inc., 2017.

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

TY - GEN

T1 - The Validation of an ACS-SSI based Online Condition Monitoring for Railway Vehicle Suspension Systems using a SIMPACK Model

AU - Liu, Fulong

AU - Gu, Fengshou

AU - Ball, Andrew

AU - Zhao, Yunshi

AU - Peng, Bo

PY - 2017/10/26

Y1 - 2017/10/26

N2 - To enhance the safe operation of modern railway vehicles, an online condition monitoring scheme is proposed for vehicle suspension systems. The core technology of the scheme is based on the average correlation signals based stochastic subspace identification (ACS-SSI) algorithm which allows system identification to be implemented reliably with output signals only that have strong noise and nonlinearity in vehicle applications. To validate the scheme, a series simulation studies were carried out based on a more realistic bogie model, developed in SIMPACK, under typical random excitations including vertical, lateral, rolling and gauging directions. ACS-SSI then applied to the signals from the model under common faults in the bogie suspensions to identify the system parameters. The agreeable results obtained by comparing the identified results with that calculated by SIMPACK shows that the proposed scheme performs reliably in obtaining the system parameters: modal frequency, damping and shape that are required for online diagnosis.

AB - To enhance the safe operation of modern railway vehicles, an online condition monitoring scheme is proposed for vehicle suspension systems. The core technology of the scheme is based on the average correlation signals based stochastic subspace identification (ACS-SSI) algorithm which allows system identification to be implemented reliably with output signals only that have strong noise and nonlinearity in vehicle applications. To validate the scheme, a series simulation studies were carried out based on a more realistic bogie model, developed in SIMPACK, under typical random excitations including vertical, lateral, rolling and gauging directions. ACS-SSI then applied to the signals from the model under common faults in the bogie suspensions to identify the system parameters. The agreeable results obtained by comparing the identified results with that calculated by SIMPACK shows that the proposed scheme performs reliably in obtaining the system parameters: modal frequency, damping and shape that are required for online diagnosis.

KW - Railway vehicle suspension

KW - Online condition monitoring

KW - ACS-SSI

UR - http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800563

U2 - 10.23919/IConAC.2017.8082030

DO - 10.23919/IConAC.2017.8082030

M3 - Conference contribution

SN - 9781509050406

BT - Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017)

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Liu F, Gu F, Ball A, Zhao Y, Peng B. The Validation of an ACS-SSI based Online Condition Monitoring for Railway Vehicle Suspension Systems using a SIMPACK Model. In Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017). Institute of Electrical and Electronics Engineers Inc. 2017 https://doi.org/10.23919/IConAC.2017.8082030