Demonstration of a Condition Monitoring Scheme for a Locomotive Suspension System

Xiaoyuan Liu; Adam Bevan

doi:10.3390/machines13080719

Demonstration of a Condition Monitoring Scheme for a Locomotive Suspension System

Xiaoyuan Liu, Adam Bevan

Research output: Contribution to journal › Review article › peer-review

1 Citation (Scopus)

Abstract

A condition-based monitoring (CBM) system provides the possibility for the railway industry to guarantee reliability by executing prompt and low-cost maintenance. In this study, a simple model-based condition monitoring strategy for the railway vehicle suspension system is demonstrated. The method is based on a recursive least-square (RLS) algorithm regarding a deterministic parametric model. The fault detection approach for the locomotive suspension system is illustrated with three diagnostic modules. Multi-body simulation data are employed to validate the feasibility of this CBM strategy. The designed diagnostic model reveals that the suspension parameter estimates are consistent with the reference values. The corresponding demonstrator provides evidence that the monitoring system has potential applications and is suitable for further development.

Original language	English
Article number	719
Number of pages	18
Journal	Machines
Volume	13
Issue number	8
DOIs	https://doi.org/10.3390/machines13080719
Publication status	Published - 12 Aug 2025

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title = "Demonstration of a Condition Monitoring Scheme for a Locomotive Suspension System",

abstract = "A condition-based monitoring (CBM) system provides the possibility for the railway industry to guarantee reliability by executing prompt and low-cost maintenance. In this study, a simple model-based condition monitoring strategy for the railway vehicle suspension system is demonstrated. The method is based on a recursive least-square (RLS) algorithm regarding a deterministic parametric model. The fault detection approach for the locomotive suspension system is illustrated with three diagnostic modules. Multi-body simulation data are employed to validate the feasibility of this CBM strategy. The designed diagnostic model reveals that the suspension parameter estimates are consistent with the reference values. The corresponding demonstrator provides evidence that the monitoring system has potential applications and is suitable for further development.",

keywords = "Condition Monitoring, Fault Diagnosis, Parameter Estimation, Locomotive Suspension, Recursive least-square, Parametric model",

author = "Xiaoyuan Liu and Adam Bevan",

note = "Funding Information: This research was funded by EU Horizon2020 Shift2Rail LOCATE (Locomotive bOgie Condition mAinTEnance) project, grant number 881805. Publisher Copyright: {\textcopyright} 2025 by the authors.",

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doi = "10.3390/machines13080719",

language = "English",

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issn = "2075-1702",

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T1 - Demonstration of a Condition Monitoring Scheme for a Locomotive Suspension System

AU - Liu, Xiaoyuan

AU - Bevan, Adam

N1 - Funding Information: This research was funded by EU Horizon2020 Shift2Rail LOCATE (Locomotive bOgie Condition mAinTEnance) project, grant number 881805. Publisher Copyright: © 2025 by the authors.

PY - 2025/8/12

Y1 - 2025/8/12

N2 - A condition-based monitoring (CBM) system provides the possibility for the railway industry to guarantee reliability by executing prompt and low-cost maintenance. In this study, a simple model-based condition monitoring strategy for the railway vehicle suspension system is demonstrated. The method is based on a recursive least-square (RLS) algorithm regarding a deterministic parametric model. The fault detection approach for the locomotive suspension system is illustrated with three diagnostic modules. Multi-body simulation data are employed to validate the feasibility of this CBM strategy. The designed diagnostic model reveals that the suspension parameter estimates are consistent with the reference values. The corresponding demonstrator provides evidence that the monitoring system has potential applications and is suitable for further development.

AB - A condition-based monitoring (CBM) system provides the possibility for the railway industry to guarantee reliability by executing prompt and low-cost maintenance. In this study, a simple model-based condition monitoring strategy for the railway vehicle suspension system is demonstrated. The method is based on a recursive least-square (RLS) algorithm regarding a deterministic parametric model. The fault detection approach for the locomotive suspension system is illustrated with three diagnostic modules. Multi-body simulation data are employed to validate the feasibility of this CBM strategy. The designed diagnostic model reveals that the suspension parameter estimates are consistent with the reference values. The corresponding demonstrator provides evidence that the monitoring system has potential applications and is suitable for further development.

KW - Condition Monitoring

KW - Fault Diagnosis

KW - Parameter Estimation

KW - Locomotive Suspension

KW - Recursive least-square

KW - Parametric model

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U2 - 10.3390/machines13080719

DO - 10.3390/machines13080719

M3 - Review article

SN - 2075-1702

VL - 13

JO - Machines

JF - Machines

IS - 8

M1 - 719

ER -

Demonstration of a Condition Monitoring Scheme for a Locomotive Suspension System

Abstract

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