A dynamic holographic modelling method of digital twin scenes for bridge construction

Wu, Jianlin; Zhu, Jun; Zhang, Jinbin; Dang, Pei; Li, Weilian; Guo, Yukun; Lin, Fei; Lai, Jianbo; You, Jigang; Xie, Yakun

doi:10.1080/17538947.2023.2229792

Cited by 24 publications

(6 citation statements)

References 66 publications

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“…Factory logistics can be revolutionized by incorporating Automated Guided Vehicles (AGVs) that track and monitor the movement of goods on the assembly line [ 34 ]. The development and application of a multi-objective AGV scheduling method based on digital twins reflect a shift toward intelligent and efficient logistics systems.…”

Section: Resultsmentioning

confidence: 99%

“…It is challenging to convert this framework into physical systems for city planners and logistics stakeholders to use and improve urban logistics. Apply digital twins for predictive maintenance of the cyclone bag filter system [58] Factory logistics can be revolutionized by incorporating Automated Guided Vehicles (AGVs) that track and monitor the movement of goods on the assembly line [34]. The development and application of a multi-objective AGV scheduling method based on digital twins reflect a shift toward intelligent and efficient logistics systems.…”

Section: Event Loggermentioning

confidence: 99%

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Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis

Li,

Zhou,

et al. 2024

Sensors

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Digital twin technology has become increasingly popular and has revolutionized data integration and system modeling across various industries, such as manufacturing, energy, and healthcare. This study aims to explore the evolving research landscape of digital twins using Keyword Co-occurrence Network (KCN) analysis. We analyze metadata from 9639 peer-reviewed articles published between 2000 and 2023. The results unfold in two parts. The first part examines trends and keyword interconnection over time, and the second part maps sensing technology keywords to six application areas. This study reveals that research on digital twins is rapidly diversifying, with focused themes such as predictive and decision-making functions. Additionally, there is an emphasis on real-time data and point cloud technologies. The advent of federated learning and edge computing also highlights a shift toward distributed computation, prioritizing data privacy. This study confirms that digital twins have evolved into complex systems that can conduct predictive operations through advanced sensing technologies. The discussion also identifies challenges in sensor selection and empirical knowledge integration.

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Section: Resultsmentioning

confidence: 99%

Section: Event Loggermentioning

confidence: 99%

Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis

Li,

Zhou,

et al. 2024

Sensors

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“…Visualization methods enhance human understanding of complex information by displaying data features in an intuitive and attractive way [29][30][31][32][33]. In order to improve users' accurate understanding of this key information when conveying diagnostic information about tunnel excavation deformation, this information must be transformed into easyto-understand visual variables [34][35][36][37][38].…”

Section: Multivariate Visual Variable Integration In the Digital Twin...mentioning

confidence: 99%

A Knowledge-Guided Intelligent Analysis Method of Geographic Digital Twin Models: A Case Study on the Diagnosis of Geometric Deformation in Tunnel Excavation Profiles

Liang,

Zhu,

Zhang

et al. 2024

IJGI

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It is essential to establish a digital twin scene, which helps to depict the dynamically changing geographical environment accurately. Digital twins could improve the refined management level of intelligent tunnel construction; however, research on geographical twin models primarily focuses on modeling and visual description, which has low analysis efficiency. This paper proposes a knowledge-guided intelligent analysis method for the geometric deformation of tunnel excavation profile twins. Firstly, a dynamic data-driven knowledge graph of tunnel excavation twin scenes was constructed to describe tunnel excavation profile twin scenes accurately. Secondly, an intelligent diagnosis algorithm for geometric deformation of tunnel excavation contour twins was designed by knowledge guidance. Thirdly, multiple visual variables were jointly used to support scene fusion visualization of tunnel excavation profile twin scenes. Finally, a case was selected to implement the experimental analysis. The experimental results demonstrate that the method in this article can achieve an accurate description of objects and their relationships in tunnel excavation twin scenes, which supports rapid geometric deformation analysis of the tunnel excavation profile twin. The speed of geometric deformation diagnosis is increased by more than 90% and the cognitive efficiency is improved by 70%. The complexity and difficulty of the deformation analysis operation are reduced, and the diagnostic analysis ability and standardization of the geographic digital twin model are effectively improved.

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“…Also, it can express bridge construction knowledge in a more intuitive way. However, the BIM model mainly focuses on physical properties and geometric features so that it is difficult to effectively express more complex knowledge and correlations and restrict the retrospective expression of historical information (Wu et al, 2023).…”

Section: Management Of Bridge Constructionmentioning

confidence: 99%

Dynamic data‐driven railway bridge construction knowledge graph update method

Lai,

Zhu,

Guo

et al. 2023

Transactions in GIS

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Effectively integrating and correlating multisource data involved in the bridge construction process is crucial for the improvement of the bridge informatization level. In the current issues of dynamic numerous data and low information sharing between different engineering departments, the traditional information management methods are inefficient in providing comprehensive and accurate data support for construction safety. Focusing on the bridge construction stage, this article proposes a dynamic data‐driven construction method of railway bridge construction knowledge graph (KG) in combination with dynamic data (materials, personnel, equipment and sensors) in the construction process and KG technology. By taking a railway bridge as a case, the study develops a prototype system and analyzes the effectiveness of bridge construction KG in material traceability, personnel and equipment management and construction safety guidance, which can provide comprehensive and accurate data support for bridge construction management and construction optimization. The results show that: (1) bridge construction KG that takes into account the dynamic features of bridge projects can effectively integrate multiple elements; (2) the bridge construction KG is dynamically updated through real‐time comparison and advance prediction based on the dynamic data collected by multi‐sensing equipment at the construction site, and can provide effective data support for guiding bridge construction safety; and (3) the construction management prototype system based on railway bridge construction KG can provide accurate data support for material traceability, personnel and equipment management and assisted risk event decision‐making. The results of the comparative experiment between the KG group and the spreadsheet group showed that utilizing the KG saved approximately 50% of time and achieved a 20% higher accuracy rate in the material traceability task compared to the spreadsheet group. In general, this study proposes a dynamic data‐driven construction method of railway bridge construction KG, which can effectively realize the effective integration and management of multisource data in the bridge construction process, provide the necessary scientific basis for fine bridge management, and help to improve bridge informatization management level.

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A dynamic holographic modelling method of digital twin scenes for bridge construction

Cited by 24 publications

References 66 publications

Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis

Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis

A Knowledge-Guided Intelligent Analysis Method of Geographic Digital Twin Models: A Case Study on the Diagnosis of Geometric Deformation in Tunnel Excavation Profiles

Dynamic data‐driven railway bridge construction knowledge graph update method

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