摘要
针对上海地铁11号线出现的车地无线通信失效的问题,提出一种基于感知学习算法的故障预测方法以改善通信状况。该方法主要采用感知学习算法(PLA)相关知识,对无线通信系统中列车运行时产生的日志大数据进行分析研究,并使用AP时间-状态曲线图、AP异常状态统计图和AP告警统计表三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,验证了这种故障预测方式的有效性。这种方式能够帮助地铁工作人员及时发现AP设备隐患,预测其故障并及时维护,从而改善通信质量、提高通信效率;同时对其他地铁沿线预测通信故障具有重要的借鉴意义。
Aiming at the failure problem of wireless communication between the metro and subway in Shanghai metro line11,a fault prediction method based on the perception learning algorithm is proposed to improve the communication state. In the method,the relevant knowledge of the perception learning algorithm(PLA)is mainly used to analyze and study the log big data generated during the metro operation in wireless communication system. Three modes of the AP time-state curve diagram,AP abnormal state statistical diagram and AP alarm statistics table are used to perform statistical and visual display of the operation state information of the trackside communication device AP. The effectiveness of the fault prediction method is verified by using the real log data provided by the subway company. The method can help the subway staff discover hidden dangers of AP devices in time,predict their faults and maintain them timely,so as to improve the communication quality and efficiency,and meanwhile,it has an important reference significance for predicting communication faults along other subways.
作者
孙亚非
郭盛
李可
SUN Yafei;GUO Sheng;LI Ke(School of Information Science and Engineering,Yanshan University,Qinhuangdao 066004,China;Department of Information Engineering,Cangzhou Technical College,Cangzhou 061000,China)
出处
《现代电子技术》
北大核心
2019年第8期94-99,共6页
Modern Electronics Technique
基金
国家自然科学基金项目(60974018)~~
关键词
地铁通信
无线通信
故障预测
感知学习算法
大数据分析
AP
subway communication
wireless communication
fault prediction
perception learning algorithm
big data analysis
AP
