摘要
城市轨道交通专业多、设备繁杂、专业性强,运维人员经验不足的情况下,无法快速定位故障原因及维修方法。利用知识图谱技术,实现从海量轨道交通历史运维数据中自动完成知识挖掘和抽取、知识消歧与融合,构建可持续、自主、完善的轨道交通设备智能运维知识,实现根据设备故障信息自动推断故障原因,并指导维修人员进行维修作业,从而确保城市轨道交通高效、安全运维。
Urban rail transit has many specialties,complicated equipment and strong professionalism.In the case of insufficient experience of operation and maintenance personnel,it is impossible to quickly locate the cause of failure and maintenance methods.In this paper,knowledge graph technology is used to realize automatic knowledge mining and extraction,knowledge disambiguation and fusion from massive historical operation and maintenance data of rail transit,and to construct sustainable and independent intelligent operation and maintenance knowledge of rail transit equipment,so as to realize automatic inference of fault causes according to equipment fault information and guide maintenance personnel to carry out maintenance operations,so as to ensure efficient and safe operation and maintenance of urban rail transit.
作者
袁超
陈超录
青怡
郭健
YUAN Chao;CHEN Chaolu;QING Yi;GUO Jian(Zhuzhou Crrc Times Electric Co.,Ltd.,Zhuzhou Hunan 412001;Qingdao Hisense Network Technology Co.,Ltd.,Qingdao Shandong 266000)
出处
《中国科技纵横》
2023年第23期30-32,共3页
China Science & Technology Overview
关键词
城市轨道交通
知识图谱
智能运维
故障分析
urban rail transit
knowledge graph
intelligent operation and maintenance
fault analysis
