摘要
针对上海轨道交通11号线出现的车地无线通信失效的问题,对无线通信故障进行了研究。主要采用机器学习PLA算法(感知机学习算法)相关知识,对无线通信系统中列车运行时产生的日志数据进行分析研究,并使用AP(无线接入点)时间-状态曲线图、AP异常状态统计图和AP告警统计表等3种方式对轨旁通信设备AP运行状态信息进行统计及可视化展示。利用地铁公司提供的真实日志数据,验证了这种故障分析方式的有效性。该分析方式能够帮助地铁工作人员及时发现AP设备隐患、故障并维护,从而改善通信质量、提高通信效率,同时对其他地铁沿线通信故障分析也具有重要的借鉴意义。
In view of the vehicle-ground wireless communication faults on Shanghai metro Line 11, the wireless communication faults are studied. The perceptron learning algorithm(PLA) is used to analyze the log data generated in wireless communication system during the train operation, three methods are adopted to conduct statistical and visual presentation of AP(access point) operation status of track-side communication device, including the AP time-state curve, AP abnormal state statistics graph, and AP alarm statistics table. Then, the real log data provided by subway companies are used to verify the effectiveness of the fault analysis method. The result shows that the method can help subway staff to discover the hidden dangers and provide maintenance of AP equipment timely, thereby improving the communication quality and efficiency. At the same time, the method provides an important reference for the communication failure analysis along other subway lines.
作者
陈宇磊
黄晓杰
邵跃堂
傅伟清
吴磊
程道来
杨明来
CHEN Yulei;HUANG Xiaojie;SHAO Yuetang;FU Weiqing;WU Lei;CHENG Daolai;YANG Minglai(Faculty of Railway Transportation,Shanghai Institute of Technology,201418,Shanghai,China)
出处
《城市轨道交通研究》
北大核心
2019年第11期88-92,96,共6页
Urban Mass Transit
基金
上海申通地铁集团有限公司项目(JS-KY14R012)
上海市科委地方院校能力建设项目(17090503500)
关键词
地铁
无线通信
故障分析
日志数据
无线接入点
机器学习
subway
wireless communication
fault analysis
log data
wireless access point(AP)
machine learning
作者简介
第一作者:陈宇磊,硕士研究生;通信作者:杨明来。
