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Optimal Metro-Rail Maintenance Strategy using Multi-Nets Modeling

机译:使用多网络建模的最佳地铁轨道维护策略

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摘要

Reliability analysis has become an integral part of system design and operating. This is especially true for systems performing critical tasks such as mass transportation systems. This explains the numerous advances in the field of reliability modeling. More recently, some studies involving the use of Bayesian Networks (BN) have been proved relevant to represent complex systems and perform reliability studies. In previous works, the generic decision support tool VirMaLab, developed to evaluate complex systems maintenance strategies, was introduced. This approach is based on a specific Dynamic BN, designed to model stochastic degradation processes and allowing any kind of state sojourn distributions along with an accurate context description: the Graphical Duration Models. This paper deals with a multi-nets extension of VirMaLab, dedicated to maintenance of metro rails. Indeed, due to fulfillment of high-performance levels of safety and availability (the latter being especially critical at peak hours), the operator needs to estimate, hour by hour its ability to detect broken rails.
机译:可靠性分析已成为系统设计和操作的组成部分。对于执行关键任务的系统(例如大众运输系统)尤其如此。这解释了可靠性建模领域的众多进步。最近,一些涉及使用贝叶斯网络(BN)的研究已被证明与代表复杂系统和进行可靠性研究有关。在以前的工作中,介绍了用于评估复杂系统维护策略的通用决策支持工具VirMaLab。这种方法基于特定的动态BN,该模型旨在对随机退化过程进行建模,并允许任何形式的状态驻留分布以及准确的上下文描述:图形持续时间模型。本文讨论了VirMaLab的多网扩展,专用于地铁轨道的维护。实际上,由于达到了高性能的安全性和可用性(后者在高峰时段尤为重要),操作员需要每小时估算其检测断轨的能力。

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