Detection and Assessment of Seismic Response of High-Speed Railway Bridges Based on Smartphone Public Participation

被引:0
|
作者
Liu, Jiaqi [1 ,2 ]
Li, Weijie [1 ,2 ]
Zhao, Chenhao [1 ,2 ]
Jing, Yicheng [1 ,2 ]
Yin, Chao [1 ,2 ]
Zhao, Xuefeng [1 ,2 ]
机构
[1] Dalian Univ Technol, Sch Infrasturct Engn, Dalian 116024, Peoples R China
[2] Dalian Univ Technol, State Key Lab Coastal & Offshore Engn, Dalian 116024, Peoples R China
基金
中国国家自然科学基金;
关键词
high-speed railway bridge; smartphones; earthquake response; Unreal Engine; structural health detection; CONTINUOUS-GIRDER BRIDGE; DAMAGE DETECTION; INSPECTION;
D O I
10.3390/buildings14072091
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The seismic response detection and operational safety assessment of high-speed railway (HSR) bridges play a crucial role in ensuring HSR systems' operational safety and reliability. Smartphones have introduced intelligent inspection tools for structural health detection, becoming a new tool for intelligent structural inspection. Combining the public and smartphones is the key to public participation in structural health detection. This study utilizes smartphone-based structural seismic response inspection technology to investigate the framework of public participation in earthquake response inspection and assessment. This system comprises the Smart Bridge Brain (SBB), which integrates data from multiple sources and systems, an assigning mechanism for public participation inspection tasks, and smartphone-based HSR bridge structural seismic response inspection technology. At the same time, the Unreal Engine 5.0 software is used to create a mixed-reality virtual simulation experimental environment to validate the feasibility of this framework. The results indicate that the intelligent optimization of task allocation by the SBB successfully assigns detection tasks to each public participant. Public participants can promptly reach predefined damage structure detection targets and rapidly inspect bridge structural seismic response indicators using smartphones. In addition, this paper also conducts a comprehensive evaluation and analysis of the detection of the work efficiency index (WEI) within the system. Furthermore, optimization strategies for the efficient execution of detection tasks are proposed based on WEI variations influenced by different factors. The system framework is expected to enhance cluster-based HSR bridges' intelligent disaster prevention and mitigation capabilities.
引用
收藏
页数:24
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