基于数字模型的重载铁路工务设备全寿命周期管理  

Life Cycle Management of Heavy Haul Railway Track Infrastructure Based on Digital Model

作　　者：代春平 DAI Chunping(Infrastructure Inspection Research Institute,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China)

机构地区：[1]中国铁道科学研究院集团有限公司基础设施检测研究所,北京100081

出　　处：《铁道建筑》2022年第8期37-41,共5页Railway Engineering

基　　金：国家能源投资集团有限责任公司科技创新项目(GJNY-20-231)。

摘　　要：为了推动智慧重载铁路建设,提升工务设备智能运维水平,采用大数据、BIM(Building Information Modeling)和GIS(Geography Information System)技术构建了工务设备全寿命周期管理系统,解决了数据孤岛等问题,实现了重载铁路工务设备数字化、精细化管理。该管理系统将以设备为核心的各类数据予以统一存储、管理和共享,并通过制定工务设备及构件的统一分类编码规则,使得桥梁、隧道的BIM模型和线路单体构件矢量图以及检测数据、设计参数、病害信息等均可综合展示,为运维管理部门提供了高效便捷的数据服务。使用神经网络等技术对设备进行状态评估及变化趋势预测,为研究工务设备状态变化规律、制定养护维修决策提供了数据支持。In order to promote the construction of intelligent heavy haul railway and improve the intelligent operation and maintenance level of track infrastructure,the big data,BIM(building information modeling)and GIS(geographic information system)technologies were used to build the life cycle management system of track infrastructure,solve the problems of data island and realize the digital and fine management of track infrastructure of heavy haul railway. The management system uniformly stores,manages and shares all kinds of data with equipment as the core,and makes BIM models of bridges and tunnels,vector diagrams of components of line monomer,as well as detection data,design parameters and disease information can be comprehensively displayed by formulating uniform classification and coding rules for track infrastructure and components,providing efficient and convenient data services for operation and maintenance management departments. Neural network and other technologies are used to evaluate the state of equipment and predict the change trend,which provides data support for studying the state change law of track infrastructure and making maintenance decisions.

关 键 词：重载铁路 数字模型 设备单体化 全寿命周期 设备履历 工务设备 BIM GIS 

分 类 号：U216.3[交通运输工程—道路与铁道工程]