[1]叶万军,成炜康,陈笑楠,等.砂卵石地层大直径盾构工程地表沉降深度学习预测*[J].中国安全生产科学技术,2023,19(8):124-129.[doi:10.11731/j.issn.1673-193x.2023.08.018]
YE Wanjun,CHENG Weikang,CHEN Xiaonan,et al.Deep learning and prediction on surface subsidence of large-diameter shield project in sandy cobble stratum[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2023,19(8):124-129.[doi:10.11731/j.issn.1673-193x.2023.08.018]
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砂卵石地层大直径盾构工程地表沉降深度学习预测*
YE Wanjun,CHENG Weikang,CHEN Xiaonan,et al.Deep learning and prediction on surface subsidence of large-diameter shield project in sandy cobble stratum[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2023,19(8):124-129.[doi:10.11731/j.issn.1673-193x.2023.08.018]
《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]
- 卷:
- 19
- 期数:
- 2023年8期
- 页码:
- 124-129
- 栏目:
- 职业安全卫生管理与技术
- 出版日期:
- 2023-08-31
文章信息/Info
- Title:
- Deep learning and prediction on surface subsidence of large-diameter shield project in sandy cobble stratum
- 文章编号:
- 1673-193X(2023)-08-0124-06
- 分类号:
- X947
- 文献标志码:
- A
- 摘要:
- 为进一步提高复杂环境下大直径盾构工程沉降预测的准确性，以成都地铁17号线为研究对象，基于深度学习方法及z-score标准化处理后的盾构掘进参数数据，采用网格搜索法找出超参数最佳组合，构建地表沉降预测模型，并通过与其他预测模型进行比较，验证所构建模型的可行性及有效性。研究结果表明：预测模型的预测结果与实测结果拟合较好，预测精度能够满足实际工程需求；当地表沉降小于20 mm时，模型预测精度最高，为93.68%。研究结果对盾构工程的安全施工具有重要的现实意义。
- Abstract:
- In order to further improve the accuracy of surface subsidence prediction for large-diameter shield projects in complex environments,taking Line 17 of Chengdu Metro as the research object,the optimal combination of hyper-parameters was found out by using the grid search method based on the deep learning method and combining with the shield tunnelling parameter data processed by z-score standardization.A prediction model of surface subsidence was established and compared with other prediction models,then the feasibility and effectiveness of the constructed model were verified.The results show that the prediction results of the prediction model are in good agreement with the measured results,and the prediction accuracy can meet the actual engineering requirements.When the surface subsidence is less than 20 mm,the prediction accuracy of the model is the highest,which is 93.68%.The research results have important practical significance for the safe construction of shield projects.
参考文献/References:
［1］吴波,许杰,黄惟,等.富水砂层刚度参数敏感性分析及地表沉降预测［J］.中国安全生产科学技 术,2020,16(9):96-102.
WU Bo,XU Jie,HUANG Wei,et al.Sensitivity analysis of stiffness parameters of water rich sand layer and prediction of surface subsidence ［J］.Journal of Safety Science and Technology,2020,16(9):96-102.
［2］陈志敏,范长海,张常书.地铁盾构下穿建筑群施工地面建筑沉降控制方案及富水砂-黏地层沉降预测方法［J］.城市轨道交通研究,2023,26(1):39-43.
CHEN Zhimin,FAN Changhai,ZHANG Changshu.Ground building settlement control scheme and prediction method for settlement in water rich sand clay strata during subway shield tunneling construction ［J］.Urban Mass Transit,2023,26(1):39-43.
［3］冯小婷,吕岩,刘婷婷,等.大粒径卵石层地铁换乘站地表沉降预测［J］.科学技术与工程,2022,22(11):4505-4515.
FENG Xiaoting,LYU Yan,LIU Tingting,et al.Prediction of ground subsidence of subway Interchange station with large grain gravel layer ［J］.Science Technology and Engineering,2022,22(11):4505-4515.
［4］夏汉庸,黄毅,尹和军,等.基于XGBoost算法的盾构施工地面沉降预测方法［J］.铁道标准设计,2023,4（11）：1-14.
XIA Hanyong,HUANG Yi,YIN Hejun,et al.Ground settlement prediction method for shield tunneling construction based on XGBoost algorithm ［J］.Railway Standard Design,2023,4（11）：1-14.
［5］邵根大.预测与实用:地铁隧道施工引起的地面沉降［J］.铁道建筑,2016(4):1-4.
SHAO Genda.Prediction and application:ground settlement caused by subway tunnel construction ［J］.Railway Architecture,2016(4):1-4.
［6］李国成,丁烈云.武汉长江隧道盾构施工引起的地表沉降预测［J］.铁道工程学报,2008(5):59-62.
LI Guocheng,DING Lieyun.Prediction of ground settlement caused by shield construction of Wuhan Yangtze River Tunnel ［J］.Journal of Railway Engineering Society,2008(5):59-62.
［7］PECK R B.Deep excavations and tunneling in soft ground.in:proceedings of the 7th international conference on soil mechanics and foundation engineering ［J］.The Sociedad Mexicana de Meca’nica de Suelos,Mexico City,1969(11):225-290.
［8］MINDLIN R D.Force at a point in the interior of a semi-infinite solid ［J］.Physics,1936,7(5):195-202.
［9］李达,孔恒,郭飞,等.土压平衡矩形顶管施工引起的地表沉降规律研究［J］.中国安全生产科学技术,2018,14(10):144-150.
LI Da,KONG Heng,GUO Fei,et al.Study on the law of ground subsidence caused by earth pressure balance rectangular pipe jacking construction ［J］.Journal of Safety Science and Technology,2018,14(10):144-150.
［10］杨益,李兴高,蒋兴起,等.粉质黏土地层盾构施工地表沉降关键参数分析与预测［J］.城市轨道交通研究,2021,24(9):98-103.
YANG Yi,LI Xinggao,JIANG Xingqi,et al.Analysis and prediction of key parameters for surface settlement during shield tunneling in silty clay layers ［J］.Urban Mass Transit,2021,24(9):98-103.
［11］窦炳珺,钟均民,赵鹏,等.硬岩地区盾构掘进地表竖向位移监测数据及数值模拟分析［J］.科学技术与工程,2022,22(25):11227-11234.
DOU Bingjun,ZHONG Junmin,ZHAO Peng,et al.Surface vertical displacement monitoring data and numerical simulation analysis of shield tunneling in hard rock areas ［J］.Science Technology and Engineering,2022,22(25):11227-11234.
［12］刘纪峰,张会芝.盾构隧道旁穿建筑物地层沉降的数值模拟分析［J］.建筑科学,2011,27(9):31-36.
LIU Jifeng,ZHANG Huizhi.Numerical simulation analysis of ground settlement of buildings passing through shield tunnels ［J］.Building Science,2011,27(9):31-36.
［13］赵东平,沈振东,王风,等.砂卵石泥岩复合地层盾构隧道施工导致的地表沉降槽宽度计算方法研究［J］.现代隧道技术,2022,59(S1):32-41.
ZHAO Dongping,SHEN Zhendong,WANG Feng,et al.Research on the calculation method of surface settlement groove width caused by shield tunnel construction in sand gravel mudstone composite strata ［J］.Modern Tunnelling Technology,2022,59(S1):32-41.
［14］唐洪亮,刘芳亮,黄永亮.膨胀土地区深基坑开挖模型试验与数值计算研究［J］.公路,2018,63(6):336-341.
TANG Hongliang,LIU Fangliang,HUANG Yongliang.Model test and numerical calculation study of deep foundation pit excavation in expansive soil area ［J］.Highway,2018,63(6):336-341.
［15］王均山,衣凡,连文博,等.软土地区地铁盾构隧道引发地表沉陷实例研究［J］.建筑结构,2022,52(S1):2871-2877.
WANG Junshan,YI Fan,LIAN Wenbo,et al.Case study on ground subsidence caused by metro shield tunnels in soft soil area ［J］.Building Structure,2022,52(S1):2871-2877.
［16］杨兵明.软土地层盾构隧道长期沉降规律及预测研究［J］.铁道工程学报,2015,32(11):87-92.
YANG Bingming.Research on long term settlement law and prediction of shield tunnels in soft soil strata ［J］.Journal of Railway Engineering Society,2015,32(11):87-92.
［17］岳岭,刘方,刘辉,等.基于人工神经网络的大直径盾构隧道施工地层变形预测分析［J］.铁道标准设计,2020,64(1):122-126.
YUE Ling,LIU Fang,LIU Hui,et al.Prediction and analysis of ground deformation during construction of large diameter shield tunnels based on artificial neural networks ［J］.Railway Standard Design,2020,64(1):122-126.
［18］崔庆龙.岩溶地层盾构施工引起地表沉降的规律及预测研究［J］.现代隧道技术,2021,58(S2):110-119.
CUI Qinglong.Research on the law and prediction of surface subsidence caused by shield tunnel construction in karst strata ［J］.Modern Tunnelling Technology,2021,58(S2):110-119.
［19］何嵘国,张孝勇,汪旭,等.基于深度学习的地铁隧道监控量测数据分析预测方法［J］.隧道建设,2021,41(S2):261-267.
HE Rongguo,ZHANG Xiaoyong,WANG Xu,et al.Analysis and prediction method of subway tunnel monitoring measurement data based on deep learning ［J］.Tunnel Construction,2021,41(S2):261-267.
［20］谢玖琪,杨平,郑杰明,等.灰色理论在水平冻结施工隧道盾构到达洞门时地表沉降预测中的应用［J］.铁道建筑,2013(3):85-88.
XIE Jiuqi,YANG Ping,ZHENG Jieming,et al.The application of grey theory in predicting surface settlement when shield tunneling reaches the tunnel portal during horizontal freezing construction ［J］.Railway Architecture,2013(3):85-88.
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备注/Memo
- 备注/Memo:
-
收稿日期： 2023-02-18
* 基金项目： 国家自然科学基金项目（42072319）
作者简介： 叶万军，博士，教授，主要研究方向为岩土工程、边坡工程、隧道工程。
通信作者： 成炜康，博士研究生，主要研究方向为隧道工程。
