支持三模态的城市轨道交通综合监控系统车站云节点的设计实现

Design and Implementation of Station Cloud Node for Integrated Monitoring System Supporting Three Modes in Urban Rail Transit

目的:城市轨道交通云平台的综合监控系统存在服务器资源配置低、运行性能差、车站调试难度大及后期数据同步困难等问题,应深入研究和解决当云平台故障或骨干网中断等情况下,车站降级综合监控系统能够满足地铁正常运营需求的关键技术。方法:针对目前存在的问题,提出了一种特殊的综合监控车站服务器——综合监控车站云节点(以下简称“车站云节点”)。通过对综合监控系统车站降级服务器功能的梳理,设计出满足车站降级功能,且部署在车站地域的车站云节点。车站云节点支持正常、调试及降级等3种模态的运行及切换,满足车站降级综合监控系统正常运行、调试和降级等3种不同的应用场景。以典型的降级场景为例,详细叙述了车站云节点从正常模态切换到降级模态的触发条件、状态切换操作流程及降级模态下的数据流。结果及结论:基于车站云节点的创新设计,降低了云平台故障或者骨干网中断等故障给综合监控系统带来的灾害,极大地提升了基于云平台的综合监控系统的可用性和健壮性。

Objective:The IMS(integrated monitoring system)of urban rail transit cloud platform faces issues such as low server resource configuration,poor operational performance,difficulty in station debugging,and challenges in subsequent data synchronization.It is essential to conduct in-depth research to address key technologies ensuring that the station downgrade IMS can meet the normal operational requirements of metro in the event of cloud platform failures or backbone network interruptions.Method:To address the existing issues,a specialized integrated monitoring station server—integrated monitoring station cloud node(hereinafter referred to as′station cloud node′)is proposed.By sorting the functionality of the IMS station downgrade server,a station cloud node is designed to meet the station downgrade functionality and is deployed in the geographical area of the station.The station cloud node supports 3 modes of operation and switching:normal,debugging,and downgrade,It caters to three different application scenarios of the station downgrade IMS,including normal operation,debugging,and downgrade.Taking a typical downgrade scenario as example,the initiative conditions for the station cloud node to switch from normal mode to downgrade mode,the state transition operation process,and the data flow under downgrade mode are detailed.Result&Conclusion:The innovative design of the station cloud node reduces the impact of cloud platform failures or backbone network interruptions on the IMS,significantly enhancing the availability and robustness of the cloud platform-based IMS.