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作者:

Liu, Zhansheng (Liu, Zhansheng.) | Meng, Xintong (Meng, Xintong.) | Xing, Zezhong (Xing, Zezhong.) | Jiang, Antong (Jiang, Antong.)

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EI Scopus SCIE

摘要:

Safety management in hoisting is the key issue to determine the development of prefabricated building construction. However, the security management in the hoisting stage lacks a truly effective method of information physical fusion, and the safety risk analysis of hoisting does not consider the interaction of risk factors. In this paper, a hoisting safety risk management framework based on digital twin (DT) is presented. The digital twin hoisting safety risk coupling model is built. The proposed model integrates the Internet of Things (IoT), Building Information Modeling (BIM), and a security risk analysis method combining the Apriori algorithm and complex network. The real-time perception and virtual-real interaction of multi-source information in the hoisting process are realized, the association rules and coupling relationship among hoisting safety risk factors are mined, and the time-varying data information is visualized. Demonstration in the construction of a large-scale prefabricated building shows that with the proposed framework, it is possible to complete the information fusion between the hoisting site and the virtual model and realize the visual management. The correlative relationship among hoisting construction safety risk factors is analyzed, and the key control factors are found. Moreover, the efficiency of information integration and sharing is improved, the gap of coupling analysis of security risk factors is filled, and effective security management and decision-making are achieved with the proposed approach.

关键词:

coupling method hoisting safety risk coupling digital twin prefabricated building hoisting

作者机构:

  • [ 1 ] [Liu, Zhansheng]Beijing Univ Technol, Dept Urban Construct, Beijing 100124, Peoples R China
  • [ 2 ] [Meng, Xintong]Beijing Univ Technol, Dept Urban Construct, Beijing 100124, Peoples R China
  • [ 3 ] [Xing, Zezhong]Beijing Univ Technol, Dept Urban Construct, Beijing 100124, Peoples R China
  • [ 4 ] [Jiang, Antong]Beijing Univ Technol, Dept Urban Construct, Beijing 100124, Peoples R China

通讯作者信息:

  • [Liu, Zhansheng]Beijing Univ Technol, Dept Urban Construct, Beijing 100124, Peoples R China

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来源 :

SENSORS

年份: 2021

期: 11

卷: 21

3 . 9 0 0

JCR@2022

ESI学科: CHEMISTRY;

ESI高被引阀值:96

JCR分区:2

被引次数:

WoS核心集被引频次: 50

SCOPUS被引频次: 61

ESI高被引论文在榜: 0 展开所有

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