Digital twin: Stability analysis for tower crane hoisting safety with a scale model

塔式起重机 工程类 塔楼 结构工程 理论(学习稳定性) 计算机科学 机器学习
作者
Weiguang Jiang,Lieyun Ding,Cheng Zhou
出处
期刊:Automation in Construction [Elsevier BV]
卷期号:138: 104257-104257 被引量:65
标识
DOI:10.1016/j.autcon.2022.104257
摘要

Unsafe hoisting behaviors are the fuse of tower crane overturning safety accident. However, the hoisting operation has a certain degree of randomness and invisibility, and it is extremely dangerous to carry out the experiment on the construction site, which makes the research on the relevant regularity very scarce. To simulate different hoisting behaviors as realistically as possible and analyze their dynamic effects on the tower crane, a digital twin (DT) framework of human–machine interaction construction activities is constructed based on the scale model in this study. Through experimental study, the stability change law of the tower crane with the incremental dynamic load is obtained based on the collapse probability level function. Experiment results show that tilt hoisting is the most dangerous behavior causing the tower crane instability. Tower crane foundation and masts are the most vulnerable components to be disturbed by unsafe hoisting behaviors, which can be used as key areas for sensor deployment. This paper can support the detection of the dangerous parts of the tower crane structure, and the monitoring system design for unsafe hoisting behaviors will be carried out in the future.
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