Abstract

Performance evaluation and maintenance planning are gaining importance with ageing rail infrastructure and increasing demand on track safety and continuous availability. The discrete/point railway assets (e.g. bridges, level crossings) together with extended track sections constitute the main railway network infrastructure. The former has important implications in train safety, riding comfort and operating expenditures due to local intensified degradation and plays a role in effective network capacity due to their large quantity. The heterogeneity in asset features and operating environment also adds difficulties to efficient maintenance planning of multiple discrete assets. The current review screens the issue to level crossings, as little concern has been engaged to this asset type, and draws together different perspectives related to their maintenance management. The systems thinking approach is integrated and two levels of asset management (i.e. micro- and macro-level) are used to structure the synthesis, which are interdependent and synergistic. Two major approaches, namely, the mechanistic and data-driven modelling are synthesised. Both contribute to the maintenance knowledge and their comparisons are elaborated. Limitations in existing studies are identified and directions for future research are provided, aiming to contribute to a more refined ‘inspection and diagnosis’ process to properly capture the local track issues and move towards system-level maintenance approach for multiple level crossings.

摘要

随着铁路基础设施老化以及对轨道安全和持续可用性的需求不断增加，性能评估和维护计划变得越来越重要。离散/点铁路资产（例如桥梁、平交道口）与延伸的轨道部分一起构成了主要的铁路网络基础设施。前者由于局部加剧退化而对列车安全、乘坐舒适性和运营支出具有重要意义，并且由于数量大而在有效网络容量中发挥作用。资产特征和运行环境的异质性也给多个离散资产的高效维护规划增加了难度。目前的审查将问题筛选到平交道口，因为对这种资产类型的关注很少，并汇集了与其维护管理相关的不同观点。系统思维方法是集成的，资产管理的两个层次（即微观和宏观层次）用于构建综合，它们是相互依赖和协同的。综合了两种主要方法，即机械建模和数据驱动建模。两者都有助于维护知识，并详细说明了它们的比较。确定了现有研究的局限性，并提供了未来研究的方向，旨在促进更精细的“检查和诊断”过程，以正确捕捉当地轨道问题，并为多个平交道口转向系统级维护方法。微观和宏观层面）用于构建相互依赖和协同的合成。综合了两种主要方法，即机械建模和数据驱动建模。两者都有助于维护知识，并详细说明了它们的比较。确定了现有研究的局限性，并提供了未来研究的方向，旨在促进更精细的“检查和诊断”过程，以正确捕捉当地轨道问题，并为多个平交道口转向系统级维护方法。微观和宏观层面）用于构建相互依赖和协同的合成。综合了两种主要方法，即机械建模和数据驱动建模。两者都有助于维护知识，并详细说明了它们的比较。确定了现有研究的局限性，并提供了未来研究的方向，旨在促进更精细的“检查和诊断”过程，以正确捕捉当地轨道问题，并为多个平交道口转向系统级维护方法。