Department of Urban Construction, Beijing University of Technology, Beijing 100124, China.
Sensors (Basel). 2022 Mar 25;22(7):2522. doi: 10.3390/s22072522.
Prefabricated buildings have advantages when it comes to environmental protection. However, the dynamics and complexity of building hoisting operations bring significant safety risks. Existing research on hoisting safety risk lacks a real-time information interaction mechanism and lacks scientific control decision-making tools based on considering the correlation between safety risks. Digital twin (DT) has the advantage of real-time interaction. This paper presents a safety risk control framework for controlling prefabricated building hoisting operations based on DT. In the case of considering the correlation of the safety risk index of hoisting, the safety risk hierarchy model of hoisting is defined in the process of building the DT model. The authors have established a Bayesian network model into the process of the integrated analysis of the digital twin mechanism model and monitoring data to realize the visualization of the decision analysis process of hoisting safety risk control. The key degree of the indirect inducement variable to direct inducement variable was calculated according to probability. The key factor leading to the occurrence of risk was found. The effectiveness of the hoisting safety risk control method is verified by a large, prefabricated building project. This method provides decision tools for hoisting safety risk control, assists in formulating effective control schemes, and improves the efficiency of information integration and sharing.
预制建筑在环境保护方面具有优势。然而,建筑吊装作业的动态性和复杂性带来了重大的安全风险。现有的吊装安全风险研究缺乏实时信息交互机制,也缺乏基于考虑安全风险相关性的科学控制决策工具。数字孪生 (DT) 具有实时交互的优势。本文提出了一种基于 DT 的预制建筑吊装作业安全风险控制框架。在考虑吊装安全风险指标相关性的情况下,在构建 DT 模型的过程中定义了吊装安全风险层次模型。作者将贝叶斯网络模型纳入数字孪生机制模型和监测数据的综合分析过程中,实现了吊装安全风险控制决策分析过程的可视化。根据概率计算了间接诱发变量对直接诱发变量的关键程度,找到了导致风险发生的关键因素。通过一个大型预制建筑项目验证了吊装安全风险控制方法的有效性。该方法为吊装安全风险控制提供了决策工具,有助于制定有效的控制方案,并提高信息集成和共享的效率。