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人工智能科学在软土地下工程施工变形预测与控制中的应用实践——理论基础、方法实施、精细化智能管理(示例)
引用本文:孙钧,温海洋.人工智能科学在软土地下工程施工变形预测与控制中的应用实践——理论基础、方法实施、精细化智能管理(示例)[J].隧道建设,2020,40(1):1-8.
作者姓名:孙钧  温海洋
作者单位:(1. 同济大学隧道及地下工程研究所, 上海 200092; 2. 上海市隧道(股份)集团公司院士工作室, 上海 200032)
摘    要:首先,介绍了基于人工神经网络的智能预测方法(多步滚动预测)和基于智能模糊逻辑法则的施工变形控制方法对策;其次,介绍了基坑施工和盾构掘进施工变形智能预测与控制案例。经过应用实践,认为智能方法的优点是: 对于结构变形位移和周边地表沉降/隆起,智能方法所得的预测值(3~5 d)与其相应实测值的精度偏差一般为5%~10%;不只是可以了解到当天已发生的信息,还可预见3~5 d将要发生的变形位移和沉降/隆起等的预测定量值;在施工变形达到超限阈值前,采用智能模糊逻辑控制法则作处理,通过调整相应的施工技术参数,即可使后续变形始终处于允许的限值之内,而无需附加额外的巨大花费,节约造价,节省工期,还可实现远程、无线、视频监控。在探讨地铁施工变形智能预测与控制的基础上,开发了盾构掘进施工中工程周边地表沉降/隆起变形的多媒体三维动态可视化仿真程序软件,研制了盾构掘进施工计算机智能管理系统。目前,上海隧道工程有限公司已在上海市沿江通道盾构施工中进行试验性应用,取得了良好的技术效益。最后,对人工智能科学发展的前景及存在的一些问题进行了探讨。

关 键 词:人工智能    神经网络    机器学习    轨道交通/地铁    地下车站深大基坑    盾构法区间隧道    施工技术参数    施工变形智能预测    智能模糊逻辑控制    精细化智能技术管理    5G网络系统  
收稿时间:2019-10-23

Application of Artificial Intelligence Science to Construction Deformation Prediction and Control of Underground Engineering in Soft Soil: Cases Study on Theoretical Foundation,Method Application and Fine Intelligent Technical Management
SUN Jun,WEN Haiyang.Application of Artificial Intelligence Science to Construction Deformation Prediction and Control of Underground Engineering in Soft Soil: Cases Study on Theoretical Foundation,Method Application and Fine Intelligent Technical Management[J].Tunnel Construction,2020,40(1):1-8.
Authors:SUN Jun  WEN Haiyang
Institution:(1. Institute of Tunnel and Underground Engineering, Tongji University, Shanghai 200092, China; 2. Academician Working Station of Shanghai Tunnel Engineering Co., Ltd., Shanghai 200032, China)
Abstract:In this paper, the construction deformation control method based on artificial neural network intelligent prediction method(multi step fluctuant prediction) and intelligent fuzzy logic is put forward firstly. And then the intelligent deformation prediction and control of foundation pit and shield tunneling are presented by cases study. The applicable results show that the advantages of the intelligent method are as follows: (1) the precision error between 3 to 5 day predicted values of structural deformation and surface settlement and monitored values is within 5%~10%; (2) the current data can be seen and the deformation/displacement and settlement in 3 to 5 days can be predicted; (3) the subsequent construction deformation can be effectively controlled within limit by adopting intelligent logic control and adjusting construction technical parameters; (4) and a great amount of money can be saved, the construction schedule can be shorted, and the remote, wireless and video monitoring can be realized. Meanwhile, the multimedia 3D dynamic visualized simulation software and the computer intelligent management system are developed based on the discussion of metro construction deformation prediction and control. The software and the system have been successfully applied to the Yanjiang Tunnel shield construction in Shanghai by Shanghai Tunnel Engineering Co.〖KG-*3〗, Ltd. which resulting in good technical benefits. Finally, the prospect and issues of artificial intelligence science are discussed.
Keywords:artificial intelligence  neural network  machine learning  rail transit/metro  deep and large foundation pit of underground station  shield tunnel  construction technical parameters  construction deformation intelligent prediction  intelligent fuzzy logic control  fine intelligent technical management  5G network system  
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