Qi Jinping, Shi Jinhui, Tao Hanqing, Yan Daqiang, Liu Xiaoyu, Li Hongwei
Research Institute, Lanzhou Jiaotong University, Lanzhou, 730070, China.
Mechatronics T&R Institute, Lanzhou Jiaotong University, Lanzhou, 730070, China.
Heliyon. 2024 May 4;10(9):e30673. doi: 10.1016/j.heliyon.2024.e30673. eCollection 2024 May 15.
To address the problem of difficult performance assessment of train control on-board system after recovery from failures, we have proposed a resilience assessment methodology that uses reliability as an indicator of system resilience. Since the system failures are time-dependent, we adopted the Discrete Time Bayesian Network method to obtain the system's reliability before and after failure. Subsequently, we used an exponential recovery model to quantify the system's performance curve during the recovery phase, and finally utilized the resilient triangle area method to quantify its resilience size. Analyzing the CTCS3-300T train control on-board system, we found that the resilience of the system with cold standby redundancy design and hot standby redundancy design were 89.44 % and 87.34 %, respectively, indicating a slight decrease in system performance after recovery from failures compared to pre-failure levels. At that time, it was necessary to adjust operational plans based on actual conditions to avoid greater impact on the railway network. This paper realizes performance resilience of train control on-board system after failure recovery, which can be applied to similar systems and provide theoretical references for realizing intelligent maintenance of the high-speed train.
为解决列车控制车载系统故障恢复后性能评估困难的问题，我们提出了一种以可靠性作为系统恢复力指标的恢复力评估方法。由于系统故障具有时间依赖性，我们采用离散时间贝叶斯网络方法来获取故障前后系统的可靠性。随后，我们使用指数恢复模型来量化恢复阶段系统的性能曲线，最后利用恢复力三角形面积法来量化其恢复力大小。通过对CTCS3-300T列车控制车载系统进行分析，我们发现采用冷备冗余设计和热备冗余设计的系统恢复力分别为89.44%和87.34%，这表明与故障前水平相比，系统故障恢复后的性能略有下降。当时，有必要根据实际情况调整运营计划，以避免对铁路网络造成更大影响。本文实现了列车控制车载系统故障恢复后的性能恢复力，可应用于类似系统，并为实现高速列车智能维护提供理论参考。
