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现代隧道技术 2023, Vol. 60 Issue (2) :62-72    DOI:
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隧道及地下工程远程自动化监测与预警系统构建研究
(中铁十九局集团第五工程有限公司,大连 116100)
Study on Construction of Remote Automatic Monitoring and Early Warning System for Tunnel and Underground Works
(China Railway 19th Bureau Group No.5 Engineering Co., Ltd., Dalian 116100)
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摘要 基于Python编程语言和大数据,构建可实现工程监测、综合预警、可视化、参数反演及实时动态分析等功能的自动化监测预警系统。该自动化监测预警系统可对施工过程中岩土体压力、位移、渗透水压等进行实时监测,并自动采集监测数据进行远程无线传输,自动存储到数据库中,借助互联网云平台进行数据共享;监测数据可供IA-BP算法模块、预警预报模块调用,采用IA-BP智能算法对数据库内监测数据进行反演及智能预测分析,并进行单项阈值和IA-BP智能算法综合对比分析,达到工程灾害预警预报目的。
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于 建
关键词隧道及地下工程   自动化监测   智能化施工   预警系统     
Abstract: Based on Python programming language and big data, an automatic monitoring and early warning system is constructed, which can realize such functions as works monitoring, comprehensive early warning, visualization, parameter inversion, and real-time dynamic analysis etc. This automatic monitoring and early warning system can monitor in real time the pressure, displacement, and seepage water pressure of rock and soil mass during the construction process, automatically acquire monitoring data for remote wireless transmission, automatically store the data in a database, and use an Internet cloud platform for data sharing. The monitoring data can be used by the IA-BP algorithm module and the early warning and prediction module. The IA-BP intelligent algorithm performs inversion and intelligent prediction analysis on the monitoring data in the database, and makes comprehensive comparison and analysis between single threshold algorithm and IA-BP intelligent algorithm, thus achieving the purpose of early warning and prediction for engineering disasters.
KeywordsTunnel and underground works,   Automatic monitoring,   Intelligent construction,   Early warning system     
基金资助:中铁十九局集团有限公司科技研发项目(21-B05).
作者简介: 于 建(1973-),男,高级工程师,主要从事桥梁及隧道施工技术研究工作,E-mail: 6444794@qq.com.
引用本文:   
于 建 .隧道及地下工程远程自动化监测与预警系统构建研究[J]  现代隧道技术, 2023,V60(2): 62-72
Yu Jian .Study on Construction of Remote Automatic Monitoring and Early Warning System for Tunnel and Underground Works[J]  MODERN TUNNELLING TECHNOLOGY, 2023,V60(2): 62-72
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