摘要
本文从地铁工程全自动驾驶技术出发,深入探讨与全自动驾驶相关的车辆、通信信号、综合监控专业的综合联动模型。为保障地铁全自动驾驶系统的安全性及高可靠度,全自动无人驾驶系统中的综合维修诊断系统需要具有较完善的自诊断能力,对中心、车站、轨旁、车载以及车–地通信等设备进行实时监督,并能够实现远程故障报警和维护信息的综合管理分析。文章提出全自动驾驶综合自动化系统设计的架构及基于状态预测的设备动态预警机制,并以地铁空调风机故障诊断为例,对风机的正常运行阶段、故障初期状态、故障高发阶段进行动态预警测试,仿真结果与现场实际情况一致,可以为检修人员提供预防处理时间,避免严重的故障事故发生,降低事故故障对运营的影响。
Based on Fully Automatic Operation（ FAO） of rail transit,this article analyzed an FAO-related model,which combined Rolling Stock,Communicating,Signaling as well as Integrated Supervisory Control System（ ISCS） as a comprehensive jointly control system. Since an FAO system required a high level of safety and reliability,the embedded integrated maintenance system was supposed to have advanced ability to diagnose and alarm any failure occurred in Operation Control Centre（ OCC）,station,trackside,car borne or communicating system in real time,and was capable to process maintenance data. The article presented a design frame regarding FAO and Traffic Control Integrated Automation System（ TIAS）,and a dynamic alarming mechanism based on device status.The tunnel fan was introduced as an example. Simulations were activated on the regular operation,pre-failure and typical failure phase for dynamic alarming testing. The testing result was in line with the reality of daily operation. The design could be an efficient vehicle to assist staff detecting failure earlier,to avoid the occurrence of severe accident and alleviate the impacts of revenue service.
作者
莫志刚
骆汉宾
MO Zhi-gang;LUO Han-bin(School of Civil Engineering and Mechanics,Huazhong University of Science and Technology,Wuhan 430074,Chin)
出处
《土木工程与管理学报》
北大核心
2018年第3期129-134,共6页
Journal of Civil Engineering and Management
基金
国家"十三五"重点研发计划先进轨道交通重点专项(2016YFB1200401-102B)
