Source Journal of Chinese Scientific and Technical Papers
Included as T2 Level in the High-Quality Science and Technology Journals in the Field of Architectural Science
Core Journal of RCCSE
Included in the CAS Content Collection
Included in the JST China
Indexed in World Journal Clout Index (WJCI) Report
TONG Xiaochao. EXPERIMENTAL RESEARCH ON INSTALLATION PERFORMANCE OF ANCHOR CHANNELS[J]. INDUSTRIAL CONSTRUCTION, 2020, 50(2): 124-129. doi: 10.13204/j.gyjz202002019
Citation: CHEN Hongda, LI Xin, YU Caizhao, HE Meng, LIU Zhansheng, TONG Li. Safety Monitoring Twin System for Three Major Building Super-Large Excavation Pits Based on Internet of Things Technology[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(5): 1-8. doi: 10.3724/j.gyjzG23111319

Safety Monitoring Twin System for Three Major Building Super-Large Excavation Pits Based on Internet of Things Technology

doi: 10.3724/j.gyjzG23111319
  • Received Date: 2023-11-13
    Available Online: 2024-06-22
  • With the rapid development of economy and urbanization, the scale and number of super-large excavation pit projects have surged. However, the construction of super-large underground space structure is faced with challenges such as complex underground environment and many risk factors, and its safety problems are becoming more and more obvious. Aiming at the complex problems faced in the construction process of ultra-large underground space structure, the paper proposed an intelligent safety monitoring system suitable for the construction of ultra-large underground space structure by introducing the Internet of Things technology and the concept of digital twin, and explored the integration mechanism of Internet of Things and digital twin. BIM technology was applied in the twin to establish the corresponding physical construction model, and multi-source heterogeneous monitoring data was collected in real time through the Internet of Things technology to realize the information interaction between the virtual construction model and the physical construction model. The real-time safety analysis of multi-source heterogeneous data was carried out with the help of the twin system, and the safety status of the structure was obtained and fed back to the application service layer. The effectiveness and practicability of the twin system in the construction of super-large excavation pits were verified by an example project.
  • [1]
    李小雪, 雷可, 谭忠盛, 等. 城市地下空间施工风险因素耦合效应研究[J]. 土木工程学报, 2021, 54(增刊1): 76-86.
    [2]
    王国林, 于富来, 柳策, 等. 深基坑地表沉降预测及控制研究现状分析[J]. 工业建筑, 2023, 53(增刊1): 387-393,382.
    [3]
    赵峰. 基于BIM的基坑工程自动化监测平台研发[J]. 煤田地质与勘探, 2018, 46(2): 151-158.
    [4]
    廖原, 乔绍财, 黄海荣, 等. 某超高层深基坑支护设计及智能监测技术的应用[J]. 桂林理工大学学报, 2023, 43(1): 100-107.
    [5]
    徐志春, 王军. 基于振弦式传感器的深基坑监测系统设计[J]. 传感器与微系统, 2015, 34(7): 79-81

    ,84.
    [6]
    张阳, 张国永, 李吉庆, 等. 基于物联网与WebGIS的深基坑在线监测平台研究[J]. 地下空间与工程学报, 2021, 17(增刊1): 328-336.
    [7]
    HASHASH Y M A, JAMMOUL M, FLEMING K L, et al. Construction monitoring for the transbay transit center excavation in San Francisco, California[G]//IFCEE 2015.2015: 2502-2511.
    [8]
    WU J J, PENG L M, LI J W, et al. Rapid safety monitoring and analysis of foundation pit construction using unmanned aerial vehicle images[J/OL]. Automation in Construction, 2021[2021-05-28].http://doi.org/10.1016/j.autcon.2021.103706.
    [9]
    韩达光, 秦国成, 周银, 等. 基于BIM和三维激光扫描在基坑监测中的应用[J]. 重庆交通大学学报(自然科学版), 2019, 38(6): 72-76,102.
    [10]
    LEE H K, SONG M K, LEE S S. Prediction of subsidence during TBM operation in mixed-face ground conditions from realtime monitoring data[J/OL]. Applied Sciences, 2021[2021-12-20].http://doi.org/10.3390/app112412130.
    [11]
    LI X, LIU X, LI C Z, et al. Foundation pit displacement monitoring and prediction using least squares support vector machines based on multi-point measurement[J]. Structural Health Monitoring, 2018, 18(3): 715-724.
    [12]
    徐文杰, 唐德泓, 谭儒蛟, 等. 数字基坑系统在深大基坑工程中的应用[J]. 岩石力学与工程学报, 2015, 34(增刊1): 3510-3517.
    [13]
    王卫东, 郑筱彦, 白明洲, 等. 城市深大基坑施工安全风险多因素耦合作用机理分析[J]. 公路, 2022, 67(3): 361-366.
    [14]
    雷升祥, 黄明利, 谭忠盛. 城市地下大空间建设风险特征和分类研究[J]. 隧道建设(中英文), 2022, 42(10): 1663-1676.
    [15]
    吕超, 彭建, 彭芳乐. 滨江超大超深基坑施工风险分析与控制[J]. 地下空间与工程学报, 2014, 10(6): 1440-1448.
    [16]
    李小雪, 谭忠盛, 雷可, 等. 城市地下大空间多因素耦合的施工风险研究 [J]. 公路, 2021, 66(12): 217-226.
    [17]
    雷升祥, 雷可, 王秀英, 等. 城市地下大空间施工重大风险多因素耦合演变模型[J]. 隧道建设(中英文), 2022, 42(8): 1331-1341.
    [18]
    裴欣茹, 安宏斌, 郭健, 等. 深大基坑复杂系统风险特征及耦合效应研究[J]. 武汉轻工大学学报, 2023, 42(5): 69-75

    ,89.
    [19]
    刘占省, 史国梁, 杜修力, 等. 数字孪生驱动的预应力钢结构安全智能控制方法[J]. 天津大学学报(自然科学与工程技术版), 2023, 56(10): 1043-1053.
    [20]
    买亚锋, 张琪玮, 沙建奇. 基于BIM+物联网的智能建造综合管理系统研究[J]. 建筑经济, 2020, 41(6): 61-64.
    [21]
    柏彬, 陈勇, 杜长青, 等. 基于物联网技术的智能安全监控建筑信息模型[J]. 工业建筑, 2020, 50(4): 175-179.
    [22]
    ZHANG M, GHODRATI N, POSHDAR M, et al. A construction accident prevention system based on the Internet of Things (IoT)[J/OL]. Safety Science, 2023[2023-01-01].http://doi.org/10.1016/j.ssci.2022.106012.
    [23]
    曹庆, 刘博, 赵鸣. 基于物联网的结构施工监测技术应用[J]. 电子测量技术, 2016, 39(4): 169-172.
    [24]
    宫志群, 王永志, 廖少明. 基于数字孪生的建设工程项目管理数字化[J/OL]. 土木工程学报,2024[2024-04-23].https://doi.org/10.

    15951/j.tmgcxb.23040317.
    [25]
    杨昊, 余芳强, 高尚, 等. 基于数字孪生的建筑运维系统数据融合研究和应用[J]. 工业建筑, 2022, 52(10): 204-210

    ,235.
  • Relative Articles

    [1]ZHU Mao, GE Chunqing, BAN Yong, ZHOU Ningyuan, XU Kang, LI Jiping. Research on Urban Building Safety Monitoring Techniques Based on InSAR[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(2): 51-57. doi: 10.3724/j.gyjzG23120809
    [2]YU Caizhao, WANG Haitao, SONG Tianshuai, ZHENG Jiarong, LIU Zhansheng, YANG Kai, LIU Junjie. A Digital Delivery Method for Large Underground Spaces Integrating Multi-source and Multi-dimensional Data[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(5): 16-24. doi: 10.3724/j.gyjzG23111320
    [3]QIN Wenbo, ZHOU Cheng, CHEN Jian, WANG Fan, LIU Wenli. Digital Twin-Based Platform Framework for Metro Bridge and Tunnel Structure Service[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(2): 43-50. doi: 10.3724/j.gyjzG24010401
    [4]DENG Xingrui, ZHANG Furong, XU Zhen, YUE Qingrui, WANG Yuxiang, HAN Guoquan, SHI Zhongqi. A Review on the Applications of Digital Twin Technology in Urban Safety[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(2): 35-42. doi: 10.3724/j.gyjzG22122605
    [5]HUANG Haifeng, YIN Yang, ZHOU Yi, YANG Didan. A Review on Digital Twin Application Research for Urban Water Security[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(2): 144-154. doi: 10.3724/j.gyjzG23120902
    [6]YU Fangqiang, XU Xiaohong, SONG Tianren, ZHANG Chunyi. Application of Intelligent Operation and Maintenance System in Cultural Venues Based on Digital Twins After Opening[J]. INDUSTRIAL CONSTRUCTION, 2023, 53(2): 1-7. doi: 10.13204/j.gyjzG22073106
    [7]WU Ying, LI Aiqun. Application and Circled Layer Scene Construction of Digital Twin Technology from Coupling Perspective of "City-Building-People"[J]. INDUSTRIAL CONSTRUCTION, 2023, 53(4): 180-189. doi: 10.13204/j.gyjzG23012403
    [8]HU Zhenzhong, LIU Yi, LIN Chao. Research Prospect of BIM-Based Information Technologies for Engineering Management[J]. INDUSTRIAL CONSTRUCTION, 2022, 52(10): 195-203. doi: 10.13204/j.gyjzG22073009
    [9]YANG Hao, YU Fangqiang, GAO Shang, XU Jinglin. Research on Data Fusion of Building Operation and Maintenance Systems Based on Digital Twins and Its Application[J]. INDUSTRIAL CONSTRUCTION, 2022, 52(10): 204-210,235. doi: 10.13204/j.gyjzG22073107
    [10]JIAO Ke, LAI Hongli, PENG Zixiang, YANG Xin, YUAN Hui, WANG Jianqiang. RESEARCH ON KEY TECHNIQUES OF SAFETY OPERATION AND MAINTENANCE SERVICE FOR EXISTING BUILDINGS IN THE WHOLE LIFE CYCLE BASED ON INTERNET OF THINGS[J]. INDUSTRIAL CONSTRUCTION, 2021, 51(10): 201-210,8. doi: 10.13204/j.gyjzg20111504
    [11]LIU Zhansheng, SHI Guoliang, WANG Jingchao. RESEARCH ON INTELLIGENT PREDICTION METHOD OF PRESTRESSED CABLE FORCE BASED ON DIGITAL TWINS[J]. INDUSTRIAL CONSTRUCTION, 2021, 51(5): 1-9,123. doi: 10.13204/j.gyjzG20110502
    [12]LIU Zhansheng, SHI Guoliang, SUN Jiajia. DIGITAL TWIN AND ITS APPLICATION IN INTELLIGENT CONSTRUCTION[J]. INDUSTRIAL CONSTRUCTION, 2021, 51(3): 184-192. doi: 10.13204/j.gyjzG20081017
    [13]BAI Bin, CHEN Yong, DU Changqing, MAO Xintong, HAN Chao, LI Dongxin, HUANG Yuntian, ZHENG Xing, WANG Leilei. RESEARCH ON INTELLIGENT SECURITY MONITORING FOR BIM BASED ONINTERNET OF THINGS TECHNOLOGY[J]. INDUSTRIAL CONSTRUCTION, 2020, 50(4): 175-179. doi: 10.13204/j.gyjz202004030
    [15]Li Qinshan, Wang Tiecheng, Zhao Hailong. THE SAFETY ANALYSIS OF SUSPENSION SUPPORT TRUSS ON TOP OF LARGE-DIAMETER SILO UNDER CONCRETE CONSTRUCTION[J]. INDUSTRIAL CONSTRUCTION, 2015, 45(1): 143-147. doi: 10.13204/j.gyjz201501029
    [16]Wang Yue-dong, Tan Zhi-yong, Liu Zhi-ming, Wen Lin-jun, Zhao Xu. THE INFORMATION MONITORING TECHNOLOGY OF THE CONSTRUCTION OF DEEP EXCAVATIONS IN COASTAL AREAS WITH COMPLICATED GEOLOGIC CONDITIONS OF SINGAPORE MARITIME MUSEUM[J]. INDUSTRIAL CONSTRUCTION, 2012, 42(9): 20-25. doi: 10.13204/j.gyjz201209005
    [17]Zhao Haiyan, Zhao Xiaoxi. CONSTRUCTION & ENVIRONMENTAL MONITORING AND ANALYZING OF DEEP FOUNDATION EXCAVATION FOR PUMP STATION OF GUANGYUAN ROAD[J]. INDUSTRIAL CONSTRUCTION, 2011, 41(6): 146-149,108. doi: 10.13204/j.gyjz201106032
    [18]Ma Jian. DESIGN OF SUPPORTING SCHEME AND CONSTRUCTION MONITORING FOR SUPER LARGE DEEP EXCAVATIONS[J]. INDUSTRIAL CONSTRUCTION, 2010, 40(9): 97-100. doi: 10.13204/j.gyjz201009025
  • Cited by

    Periodical cited type(1)

    1. 刘德强. 物联网技术在装配式住宅建筑现场安全管理中的应用. 住宅与房地产. 2024(35): 116-118 .

    Other cited types(2)

  • Created with Highcharts 5.0.7Amount of accessChart context menuAbstract Views, HTML Views, PDF Downloads StatisticsAbstract ViewsHTML ViewsPDF Downloads2024-052024-062024-072024-082024-092024-102024-112024-122025-012025-022025-032025-04051015202530
    Created with Highcharts 5.0.7Chart context menuAccess Class DistributionFULLTEXT: 7.7 %FULLTEXT: 7.7 %META: 90.5 %META: 90.5 %PDF: 1.8 %PDF: 1.8 %FULLTEXTMETAPDF
    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 23.7 %其他: 23.7 %其他: 0.6 %其他: 0.6 %上海: 3.6 %上海: 3.6 %佛山: 1.2 %佛山: 1.2 %保定: 1.2 %保定: 1.2 %信阳: 0.6 %信阳: 0.6 %兰州: 0.6 %兰州: 0.6 %北京: 4.7 %北京: 4.7 %南京: 3.6 %南京: 3.6 %厦门: 0.6 %厦门: 0.6 %合肥: 1.8 %合肥: 1.8 %嘉兴: 0.6 %嘉兴: 0.6 %天津: 1.8 %天津: 1.8 %广州: 0.6 %广州: 0.6 %廊坊: 1.2 %廊坊: 1.2 %张家口: 2.4 %张家口: 2.4 %成都: 3.0 %成都: 3.0 %扬州: 1.2 %扬州: 1.2 %日照: 0.6 %日照: 0.6 %沈阳: 0.6 %沈阳: 0.6 %深圳: 0.6 %深圳: 0.6 %温州: 0.6 %温州: 0.6 %漯河: 3.6 %漯河: 3.6 %潍坊: 0.6 %潍坊: 0.6 %石家庄: 1.8 %石家庄: 1.8 %芒廷维尤: 29.6 %芒廷维尤: 29.6 %芝加哥: 1.2 %芝加哥: 1.2 %西宁: 0.6 %西宁: 0.6 %西安: 3.0 %西安: 3.0 %贵阳: 0.6 %贵阳: 0.6 %运城: 3.0 %运城: 3.0 %长沙: 1.2 %长沙: 1.2 %其他其他上海佛山保定信阳兰州北京南京厦门合肥嘉兴天津广州廊坊张家口成都扬州日照沈阳深圳温州漯河潍坊石家庄芒廷维尤芝加哥西宁西安贵阳运城长沙

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (152) PDF downloads(4) Cited by(3)
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return