Development of a digital twin-driven bridge construction safety monitoring system

The construction phases of bridges involve a wide range of elements and tasks, generating a vast amount of data in terms of type and volume. Traditional manual and document-based methods are no longer sufficient for effective and accurate project management. Consequently, more comprehensive and systematic management approaches are required. This study proposes a three-dimensional digital twin information display platform that links with the actual state of the structure, facilitating bridge construction monitoring and safety warning through the integration of digital twin technology with multi-source monitoring information. A dynamic multi-resolution digital twin model for bridge construction has been established with a bridge digital model and structural finite element model. Then a structural evaluation and warning method focusing on key stress and deformation indicators has been comprehensively formulated. A comprehensive digital twin information monitoring and management system platform has been developed for bridge construction, complete with a feedback mechanism for warning information. The experimental case application in the Zhanlin Yellow River Bridge construction process demonstrates that this method enables flexible management of the construction process and dynamic evaluation of safety status. These advancements contribute to ensuring bridge construction safety and provide administrators with a digital, real-time online management platform.

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Publication Details

Journal
Proceedings of the Institution of Civil Engineers - Engineering Sustainability
Published
2025-04-18
DOI
https://doi.org/10.1680/jensu.24.00136
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Development of a digital twin-driven bridge construction safety monitoring system

Wenming Su, Jinqiao Chen, Ying Huang, Ben Zhang et al.
Proceedings of the Institution of Civil Engineers - Engineering Sustainability
Occupational Health and Safety Research
article

Development of a digital twin-driven bridge construction safety monitoring system

Wenming Su, Jinqiao Chen, Ying Huang, Ben Zhang, Sheng Fan
article en

Abstract

The construction phases of bridges involve a wide range of elements and tasks, generating a vast amount of data in terms of type and volume. Traditional manual and document-based methods are no longer sufficient for effective and accurate project management. Consequently, more comprehensive and systematic management approaches are required. This study proposes a three-dimensional digital twin information display platform that links with the actual state of the structure, facilitating bridge construction monitoring and safety warning through the integration of digital twin technology with multi-source monitoring information. A dynamic multi-resolution digital twin model for bridge construction has been established with a bridge digital model and structural finite element model. Then a structural evaluation and warning method focusing on key stress and deformation indicators has been comprehensively formulated. A comprehensive digital twin information monitoring and management system platform has been developed for bridge construction, complete with a feedback mechanism for warning information. The experimental case application in the Zhanlin Yellow River Bridge construction process demonstrates that this method enables flexible management of the construction process and dynamic evaluation of safety status. These advancements contribute to ensuring bridge construction safety and provide administrators with a digital, real-time online management platform.

Proceedings of the Institution of Civil Engineers - Engineering SustainabilityVol. 178(6)
Southeast University (BD), Improvement Service (GB), Shandong Xiehe University (CN), Analysis and Testing Centre (CN), Intelligent Health (United Kingdom) (GB), Detection Limit (United States) (US), Southeast University (CN)
Openalex Percentile: Top 89%
Occupational Health and Safety Research
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