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A modelling approach for railway overhead line equipment asset management

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  • Kilsby, Paul
  • Remenyte-Prescott, Rasa
  • Andrews, John

Abstract

The Overhead Line Equipment (OLE) is a critical sub-system of the 25kV AC overhead railway electrification system. If OLE asset management strategies can be evaluated using a whole lifecycle cost analysis that considers degradation processes and maintenance activities of the OLE components, the investment required to deliver the level of performance desired by railway customers and regulators can be based on evidence from the analysis results. A High Level Petri Net (HLPN) model, proposed in this paper, is used to simulate the degradation, failure, inspection and maintenance of the main OLE components and to calculate various statistics, associated with the cost and reliability of the system over its lifecycle. The HLPN considers all the main OLE components in a single model and it can simulate fixed frequency inspections and condition-based maintenance regimes. In order to allow the relevant processes to be modelled accurately and efficiently, the HLPN features are used, such as specific data about individual components is taken account of in the general model. The HLPN, developed using international standards, is described in detail and a framework of its analysis for reliability and lifecycle cost evaluation is proposed. In this novel whole system model different OLE component types and their instances on a line are modelled simultaneously, and the dependencies are considered in terms of opportunistic inspection and maintenance. An example HLPN for the catenary wire is used to illustrate the model, and an application of the methodology for whole lifecycle cost evaluation of a two-mile OLE line is presented.

Suggested Citation

  • Kilsby, Paul & Remenyte-Prescott, Rasa & Andrews, John, 2017. "A modelling approach for railway overhead line equipment asset management," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 326-337.
    • Handle: RePEc:eee:reensy:v:168:y:2017:i:c:p:326-337
    DOI: 10.1016/j.ress.2017.02.012
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    Citations

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    Cited by:

    1. Xu, Ren-Hong & Lai, Yung-Cheng & Huang, Kwei-Long, 2021. "Decision support models for annual catenary maintenance task identification and assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    2. Yuanchen Zeng & Dongli Song & Weihua Zhang & Bin Zhou & Mingyuan Xie & Xiaoyue Qi, 2021. "Risk assessment of wheel polygonization on high-speed trains based on Bayesian networks," Journal of Risk and Reliability, , vol. 235(2), pages 182-192, April.
    3. Liu, Xinyang & Zheng, Zhuoyuan & Büyüktahtakın, İ. Esra & Zhou, Zhi & Wang, Pingfeng, 2021. "Battery asset management with cycle life prognosis," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    4. Braga, Joaquim A.P. & Andrade, António R., 2021. "Multivariate statistical aggregation and dimensionality reduction techniques to improve monitoring and maintenance in railways: The wheelset component," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    5. Wu, Shaomin & Do, Phuc, 2017. "Editorial," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 1-3.
    6. Wang, Jian & Gao, Shibin & Yu, Long & Ma, Chaoqun & Zhang, Dongkai & Kou, Lei, 2023. "A data-driven integrated framework for predictive probabilistic risk analytics of overhead contact lines based on dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 235(C).

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