Risk assessment of complex footbridge based on Dempster-Shafer evidence theory using Fuzzy matter-element method

被引:6
|
作者
Lu, Pengzhen [1 ]
Zhou, Yutao [1 ,2 ]
Wu, Ying [3 ]
Li, Dengguo [1 ]
机构
[1] Zhejiang Univ Technol, Hangzhou 310014, Zhejiang, Peoples R China
[2] Univ Manchester, Dept Mech Aerosp & Civil Engn, Dynam Lab, Manchester M13 9PL, England
[3] Jiaxing Nanhu Univ, Jiaxing 314001, Zhejiang, Peoples R China
关键词
Footbridge; Risk assessment; Multi-source information fusion; Fuzzy matter-element method; Improved Dempster evidence theory; MANAGEMENT; SYSTEM; BIM; SAFETY; PROJECTS;
D O I
10.1016/j.asoc.2022.109782
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Owing to the landscapes of cities and the requirements of subchannels, the construction of large -span footbridges is complex and extremely risky. These risks may lead to the collapse of a footbridge during construction, resulting in casualties and other catastrophic consequences, delays in projects and significant property losses, and potential safety hazards during follow-up maintenance. At present, China's urban footbridge construction has not been included in the overall urban construction category, and its risk assessment is static and temporary, mainly relying on the subjective judgment of experts and construction personnel, and the different cases are difficult to learn from each other. To address this issue, a new risk assessment method and a novel system quality management framework are proposed herein. In this system, real-time engineering quality data under 4M1E (Man, Method, Material, Machine, Environment) framework is used to replace traditional risk factors. An improved Dempster-Shafer theory is adopted to effectively combine heterogeneous data from the 4M1E framework and calculate the dynamic total risk index. Finally, the proposed method is verified. The research results show that the new system can predict the risk level of each stage of bridge construction objectively and effectively by using real-time monitoring data, and has high robustness in different project testing.(c) 2022 Elsevier B.V. All rights reserved.
引用
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页数:16
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