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

Author:

Liu Jiaqi12,Li Weijie12ORCID,Zhao Chenhao12,Jing Yicheng12,Yin Chao12,Zhao Xuefeng12ORCID

Affiliation:

1. School of Infrasturcture Engineering, Dalian University of Technology, Dalian 116024, China

2. State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China

Abstract

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.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

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