摘要
研究目的:随着基于信息化、智能化技术"新基建"的发展,大跨桥梁健康监测系统的应用更加广泛。本文依托某大跨全钢结构斜拉桥,通过深度融合深度学习算法、自动化实时检算以及BIM驱动的信息载体等技术,探索桥梁运营维护的智能化决策实践,提升桥梁智慧化养护水平和资产管理质量。研究结论:(1)研发的系统可实现Midas civil全功能、全过程的自动化操作,基于云服务,可极大提高实时分析的计算效率;(2)基于BP神经网络算法创建大跨径桥梁结构响应预测元模型,准确率均超过90%,可替代有限元计算实现快速、有效的结构响应分析和状态评估;(3)提出了将元代理模型集成于BIM驱动的桥梁健康监测系统为实时结构性能评估和应急响应提供技术支撑;(4)本研究成果可为桥梁智能化监测运营提供借鉴与参考。
Research purposes: With the development of "new infrastructure" based on information and intelligent technology, the application of long-span bridge health monitoring system is more extensive. Based on a long-span cable-stayed bridge with steel structure, the intelligent decision-making practice of bridge operation and maintenance is explored through depth learning integration of algorithm, automatic real-time checking and BIM driven information carrier, to improve the intelligent maintenance level and asset management quality of the bridge.Research conclusions:(1) The developed system can realize the full function and automatic operation of Midas civil. Based on cloud services, it can greatly improve the computing efficiency of real-time analysis.(2) Based on BP neural network algorithm to create long-span bridge structure response prediction element model, the accuracy is more than 90%, which can replace the finite element calculation to achieve fast and effective structural response analysis and state evaluation.(3) The meta-agent model is integrated into BIM driven bridge health monitoring system to provide technical support for real-time structural performance evaluation and emergency response.(4) The research results can provide reference for intelligent monitoring operation of bridge.
作者
田壮
樊启武
王昌杰
TIAN Zhuang;FAN Qiwu;WANG Changjie(China Railway Eryuan Engineering Group Co.Ltd,Chengdu,Sichuan 610031,China;Nuclear Industry Southwest Geotechnical Investigation&Design Institute Co.Ltd,Chengdu,Sichuan 610041,China)
出处
《铁道工程学报》
EI
北大核心
2021年第6期47-52,共6页
Journal of Railway Engineering Society
关键词
BP神经网络
结构响应预测
验算自动化
桥梁健康监测系统
BP neural network
structural response prediction
checking automation
bridge health monitoring system
