基于贝叶斯网络的CTCS-3级列控车载系统韧性

为弥补现有指标的不足，引入韧性作为非常态事件下CTCS-3级（China train control system-3）列控车载子系统运行稳定性的测度指标. 提出了车载子系统韧性量化评估方法，构建了基于贝叶斯网络（Bayesian network, BN）的韧性评估模型，并定义了5种基于韧性的部件重要度指标；进一步利用贝叶斯网络双向推理功能，计算了车载子系统在不同扰动情景下的韧性及部件重要度指标. 研究结果表明:韧性可全面描述车载子系统抵御扰动和从扰动中恢复的能力，非常态事件扰动下，韧性与可用性指标存在明显差异；不同扰动情景下系统韧性明显不同，扰动发生时，车载子系统面临磁暴影响时的韧性为0.8017，而遭遇雷电时的韧性为0.8819，面临冰雪扰动时的韧性为0.9880；部件重要度存在情景依赖，同一部件在不同扰动情景下重要度排序可能不同，且可能随时间动态变化. 

Resilience Assessment Based on Bayesian Network for on-Board Subsystem of CTCS-3 Train Control System

To make up the deficiency of existing indexes, resilience is introduced as the operation stability index for CTCS-3 (China train control system-3) on-board subsystem under abnormal events. The quantitative evaluation method of on-board subsystem resilience is proposed, the resilience evaluation model based on Bayesian network (BN) is constructed, and five kinds of component importance indexes based on resilience are defined. The bi-directional reasoning function of Bayesian network is used to evaluate the resilience of on-board subsystem under different disturbances and calculate the component importance indexes. The results show that, the resilience index can fully describe the capability of on-board subsystem to resist disturbance or recover from disturbance, and under the disturbance of abnormal events, resilience and availability indexes have marked differences. Different disturbance scenarios lead to obviously different resilience. When disturbance occurs, the resilience of the on-board subsystem is 0.8017 when it is affected by magnetic storm, 0.8819 when it is affected by thunder, and 0.9880 when it is disturbed by snow and ice. The component importance depends on the scenario, specifically, the same component may be varied in the importance ranking in different disturbance scenarios, and may change dynamically with time.