摘要
在铁路机务数据信息共享过程中,信息集成平台存在数据查询时间过长的问题,对此提出基于人工智能的铁路机务数据信息集成平台设计。优化设计信号处理器和稳压器电源,采用三级数据整合模式,结合双向映射策略,建立铁路机务数据仓库。利用分布式链路结构和管理域原理,引入分布式数据采集技术,实时采集铁路机务数据信息并将其存放于仓库内。运用人工智能分支中的IFB树结构,构建高效数据查询模型,通过SOA与ESB架构,实现机务数据集成。平台测试结果表明,铁路机务数据信息集成平台运行过程中,平均查询时间为0.18 s,满足了数据集成管理的时效性要求。
In the data information sharing of railway maintenance,the information integration platform has the problem that the data query time is too long,a railway maintenance data integration platform based on artificial intelligence is designed.The signal processor and voltage regulator power supply are optimized,and the railway maintenance data warehouse is established by using three-level data integration mode and bidirectional mapping strategy.The distributed data acquisition technology is introduced to collect real-time railway maintenance data information and store it in the warehouse by using distributed link structure and management domain principle.The IFB tree structure in the artificial intelligence branch is used to build an efficient data query model,and the aircraft maintenance data integration is realized by SOA and ESB architecture.The platform test results show that the average query time of the railway maintenance data integration platform is 0.18 s during operation,which meets the timeliness requirements of data integration management.
作者
单俊强
李海涛
邢国栋
张虎
SHAN Junqiang;LI Haitao;XING Guodong;ZHANG Hu(Locomotive Branch of Guoneng Baoshen Railway Group Co.,Ltd.,Ordos 017000,China;Anhui Bofei Electronic Co.,Ltd.,Hefei 230000,China)
出处
《微型电脑应用》
2023年第10期226-229,共4页
Microcomputer Applications
关键词
人工智能
铁路机务数据
信息采集
数据管理
查询优化
artificial intelligence
railway locomotive data
information collection
data management
query optimization
