Research on reliability analysis of high-speed railway traction substation system under common cause failures

Jiaxu Chen, Shanshan Yan and Xuqi Liu

Journal of Risk and Reliability, 2025, vol. 239, issue 5, 1164-1177

Abstract: The reliability of the system is influenced by the common cause failure mode and the multi-state characteristic. This paper proposes an improved multi-state multi-value decision diagram method to analyze the reliability of high-speed railway traction substation systems. According to the requirements of safety-critical system reliability analysis, this paper begins with an analysis of the system structure and unit module status, comprehensively considering the influence of common cause failures and multi-state characteristics. In this paper, we design the principle of transforming the fault tree model into a binary decision diagram model. Fully considering common cause failures, we extend the model to a multi-state multi-value decision diagram and provide a reliability and importance model calculation method based on state probabilities. The results indicate that this method can accurately and efficiently calculate the reliability level of the high-speed railway traction substation system, effectively identifying key components and weak links within the system. By utilizing visual models, the mechanism of common cause failure in multi-state system can be explored.

Keywords: Reliability analysis; importance analysis; multi-state multi-value decision diagram; common cause failure; high-speed railway traction substation (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1748006X241291129 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:239:y:2025:i:5:p:1164-1177

DOI: 10.1177/1748006X241291129

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().