随着铁路行业加速向数字化、智能化、信息化转型,传统路基建、运、维监测中的数据管理方法和可视化水平已无法满足未来发展的需求.为解决这一困境,提出1套基于3层浏览器/服务器(Browser/Server,B/S)架构的高铁路基监测展示平台总体构建方案,以实现监测数据和工程数据的高效集成;使用Revit软件建立传感器实体模型,基于工业基础类(Industry Foundation Classes,IFC)标准实现传感器属性信息扩展,以Java语言为中介实现IFC文件与MySQL数据库表的精准映射,并通过设置约束关联其他工程信息;利用建筑信息模型(Building Information Modeling,BIM)软件创建集成传感器的高铁路基模型,通过轻量化处理并利用Three.js引擎实现该模型在网页端的可视化展示;通过进一步关联传感器模型和数据库中的监测信息,实现监测数据的实时展示和超限示警定位功能.结果表明:该展示平台的建立可帮助相关人员快速掌握监测项目资料,动态精准评估建、运、维过程中路基的状态,从而达到促进各方交流协作和辅助决策实施的目的.
Abstract
As the railroad industry accelerates its transition towards digitalization,intelligence,and informatization,traditional approaches to data management and visualization for subgrade construction,operation,and maintenance monitoring have become inadequate for future development needs.To address this issue,a comprehensive framework for a high-speed railway subgrade monitoring display platform,based on a three-tier Browser/Server(B/S)architecture,is proposed to efficiently integrate monitoring and engineering data.The platform utilizes Revit software to create sensor entity models and extend sensor attribute information based on the Industry Foundation Classes(IFC)standard.Java is employed as an intermediary to accurately map IFC files to MySQL database tables and sets constraints to correlate with other engineering information.A high-speed railway subgrade model integrated with sensors is developed using Building Information Modeling(BIM)software.This model is then visualized on a web platform through lightweight processing and the Three.js engine.By connecting the sensor models with the monitoring data stored in the database,the platform enables real-time data display and provides over-limit warning and location functions.The results show that this display platform allows stakeholders to swiftly access monitoring data and supports dynamic,accurate assessments of subgrade conditions throughout the construction,operation,and maintenance phases.This approach enhances communication and collaboration among various parties and supports informed decision-making processes.
维普
万方数据