摘要
针对地铁列车部件因状态耦合作用而相互影响的问题,提出了一种基于模式识别的地铁列车状态耦合分析系统设计方法。该方法通过轮轨耦合分析、弓网耦合分析及部件状态特征识别技术,将异常特征进行模式抽取,获取导致异常特征的故障原因。结合某地铁列车,将该方法应用于所开发的服役安全保障系统。应用情况表明,该方法通过工况模式识别和特征耦合分析,可有效地降低干扰并获取异常特征信息,从而能够准确分析故障原因,为快速定位和精准维修提供技术支持。
Aiming at the state of subway train components interacts due to coupling,a design method of metro train state coupling analysis system based on pattern recognition is proposed. The method extracts the anomalous features through wheel-rail coupling analysis,bow-net coupling analysis and component state feature recognition technology,and acquires the faults caused abnormal features. Combined with the train of a subway company,the service security system is designed and developed. The research results show that the method can obtain the anomaly features information through the condition pattern recognition and feature coupling analysis,and effectively reduce the interference by obtaining the anomalous features to analyze the fault causes,so as to lay the foundation for rapid positioning and accurate maintenance.
作者
李兆新
胡林桥
LI Zhaoxin;HU Linqiao(School of Electronics and Informa tion,South China University of Technology,510308,Guang zhou,China)
出处
《城市轨道交通研究》
北大核心
2020年第4期81-84,共4页
Urban Mass Transit
关键词
地铁列车
状态耦合分析
模式识别
故障分析
metro train
state coupling analysis
pattern rec-ognition
failure analysis
