大数据下的结构性态监测信息管理系统设计与应用

论述了一种适用于处理海量监测数据的结构性态监测信息管理系统(MIMS)的设计方案.基于三层浏览器/服务器架构搭建软件系统，利用多服务器协同工作机制提升系统性能.应用大数据技术，充分考虑海量监测数据对数据管理系统的高要求，选用MongoDB数据库作为数据管理平台，论述了数据库结构和采用的数据格式.最后以宁波南站结构性态监测为例，展示了系统的实现效果.结果表明该系统具有很好的扩展性和通用性，每天可接收远程数据约10 GB，能实现对海量监测数据的实时吞吐和高效组织管理.
An information management system for structural behavior monitoring, named MIMS, was developed based on big data technology. The system performance was improved by using three layered browser/server architecture and multi-server coordination mechanism. To satisfy the requirements of big data processing, mongoDB database was employed in the data management platform, and the structure and format of the database were discussed. The developed system was applied to the structural behavior monitoring of Ningbo South Station, and the interfaces were illustrated. The application results of the system show that approximately 10 GB data can be remotely received every day, and the massive monitoring data can be processed efficiently.