摘要
动车组故障分析对动车组事前维修有着重要的意义,利用知识图谱技术对动车组故障信息进行知识管理,可有效地提升动车组故障智能化水平。针对一段时间内复兴号的故障数据进行研究,提出了一种自顶向下的动车组故障知识图谱构建方法。首先对故障数据进行分析,针对数据存在的多源异构的问题,提出动车组故障数据模型。其次将故障数据采用D2RQ工具,利用R2RML标准将其转化成RDF三元组形式。最后通过映射将三元组存入Neo4j图数据存储工具中。该知识图谱已经将研究对象中大部分信息进行了映射存储。
Failure analysis of EMU has great significance to the pre maintenance of EMU.The knowledge management of EMU fault information by using knowledge map technology can effectively improve the intelligent level of EMU fault.Based on the fault data of Fuxing train for a period of time,a top-down fault knowledge map construction method of EMU is proposed.Firstly,the fault data is analyzed.Aiming at the problem of multi-source and heterogeneous data,the data model of EMU fault domain is proposed.After that,the fault data is transformed into RDF triples by using D2RQ tool and R2RML standard.Finally,the triples are stored in Neo4j graph data storage tool through mapping.The knowledge map has mapped and stored most of the information in the research object.
作者
韩子威
朱建生
HAN Ziwei;ZHU Jiansheng(Postgraduate Department,China Academy of Railway Sciences,Beijing 100081,China;Institute of Computing Technology,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China)
出处
《铁道机车车辆》
北大核心
2023年第4期17-22,共6页
Railway Locomotive & Car
基金
中国铁道科学研究院集团有限公司青年专项(2021YJ182)。
