Digital Twin-Based Safety Risk Coupling of Prefabricated Building Hoisting

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.

[1]  Andrew Y. C. Nee,et al.  Digital twin driven prognostics and health management for complex equipment , 2018 .

[2]  Tuan Ngo,et al.  A review on modular construction for high-rise buildings , 2020 .

[3]  Tzung-Pei Hong,et al.  Efficient updating of discovered high-utility itemsets for transaction deletion in dynamic databases , 2015, Adv. Eng. Informatics.

[4]  Matthew R. Hallowell,et al.  Critical Success Factors for Construction Safety: Review and Meta-Analysis of Safety Leading Indicators , 2019, Journal of Construction Engineering and Management.

[5]  Geoffrey Qiping Shen,et al.  An Internet of Things-enabled BIM platform for on-site assembly services in prefabricated construction , 2018 .

[6]  Risk prediction and early warning for air traffic controllers’ unsafe acts using association rule mining and random forest , 2021 .

[7]  Neda Masoud,et al.  Integrated digital twin and blockchain framework to support accountable information sharing in construction projects , 2021, Automation in Construction.

[8]  Lieyun Ding,et al.  Development of web-based system for safety risk early warning in urban metro construction , 2013 .

[9]  Yong Fan,et al.  The research on 220GHz multicarrier high-speed communication system , 2020, China Communications.

[10]  Cheng Zhou,et al.  Quantifying the evolution of settlement risk for surrounding environments in underground construction via complex network analysis , 2020 .

[11]  Arto Kiviniemi,et al.  A review of risk management through BIM and BIM-related technologies , 2017 .

[12]  Ali Mostafavi,et al.  A simulation-based framework for concurrent safety and productivity improvement in construction projects , 2018 .

[13]  Ying Zhou,et al.  Using Bayesian network for safety risk analysis of diaphragm wall deflection based on field data , 2018, Reliab. Eng. Syst. Saf..

[14]  Pengcheng Xiang,et al.  Risk Assessment of High-Speed Rail Projects: A Risk Coupling Model Based on System Dynamics , 2020, International journal of environmental research and public health.

[15]  Tao Shi,et al.  A Data-Driven Approach to Improve the Operation and Maintenance Management of Large Public Buildings , 2019, IEEE Access.

[16]  Heikki Laitinen,et al.  Construction safety risk assessment with introduced control levels , 2018 .

[17]  Aviad Shapira,et al.  AHP-based analysis of the risk potential of safety incidents: Case study of cranes in the construction industry , 2017 .

[18]  Ken Cai,et al.  LBS Meets Blockchain: An Efficient Method With Security Preserving Trust in SAGIN , 2021, IEEE Internet of Things Journal.

[19]  Jhareswar Maiti,et al.  Identifying patterns of safety related incidents in a steel plant using association rule mining of incident investigation reports , 2014 .

[20]  Zhang Taotao.  Research on formation mechanism of coupled disaster risk , 2013 .

[21]  Branka Vucetic,et al.  A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions , 2020, IEEE Communications Surveys & Tutorials.

[22]  Fei Tao,et al.  Digital twin-driven product design, manufacturing and service with big data , 2017, The International Journal of Advanced Manufacturing Technology.

[23]  Seyyed Amin Terouhid,et al.  Safety concerns related to modular/prefabricated building construction , 2017, International journal of injury control and safety promotion.

[24]  Bhargav Dave,et al.  A framework for integrating BIM and IoT through open standards , 2018, Automation in Construction.

[25]  Geoffrey Qiping Shen,et al.  Customization of on-site assembly services by integrating the internet of things and BIM technologies in modular integrated construction , 2021 .

[26]  Liu Qiang,et al.  A multi-server information-sharing environment for cross-party collaboration on a private cloud , 2017 .

[27]  Hanbin Luo,et al.  Cyber-physical-system-based safety monitoring for blind hoisting with the internet of things: A case study , 2019, Automation in Construction.

[28]  Edward Corry,et al.  Building performance evaluation using OpenMath and Linked Data , 2018, Energy and Buildings.

[29]  Carsten Maple,et al.  Incremental Algorithm for Association Rule Mining under Dynamic Threshold , 2019, Applied Sciences.

[30]  Wenlong Shi,et al.  Experimental Investigation and Error Analysis of High Precision FBG Displacement Sensor for Structural Health Monitoring , 2020 .

[31]  Kaili Xu,et al.  Causation Analysis of Risk Coupling of Gas Explosion Accident in Chinese Underground Coal Mines , 2019, Risk analysis : an official publication of the Society for Risk Analysis.

[32]  Ke Chen,et al.  Bridging BIM and building: From a literature review to an integrated conceptual framework , 2015 .

[33]  Jia-Rui Lin,et al.  Automating closed-loop structural safety management for bridge construction through multisource data integration , 2019, Adv. Eng. Softw..

[34]  Michael W. Grieves,et al.  Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems , 2017 .

[35]  Peter E. D. Love,et al.  Combining association rules mining with complex networks to monitor coupled risks , 2019, Reliab. Eng. Syst. Saf..

[36]  Yue Pan,et al.  A BIM-data mining integrated digital twin framework for advanced project management , 2021 .

[37]  Hongzhe Dai,et al.  A Wavelet Support Vector Machine‐Based Neural Network Metamodel for Structural Reliability Assessment , 2017, Comput. Aided Civ. Infrastructure Eng..

[38]  Lieyun Ding,et al.  Safety barrier warning system for underground construction sites using Internet-of-Things technologies , 2017 .

[39]  Jianping Zhang,et al.  Development and Implementation of an Industry Foundation Classes‐Based Graphic Information Model for Virtual Construction , 2014, Comput. Aided Civ. Infrastructure Eng..

[40]  José Rogan,et al.  Non-universal critical exponents in earthquake complex networks , 2018 .

[41]  Gang Qu,et al.  Voltage Over-Scaling-Based Lightweight Authentication for IoT Security , 2021, IEEE Transactions on Computers.

[42]  P. G. Scholar,et al.  EFFECTIVE TECHNIQUES IN COST OPTIMIZATION OF CONSTRUCTION PROJECT: AN REVIEW , 2015 .

[43]  Zhansheng Liu,et al.  Digital Twin-based Safety Evaluation of Prestressed Steel Structure , 2020 .