BIM-based mixed reality application for bridge inspection
Traditional bridge inspection methods have limitations, driving the need for advanced techniques. The primary objective of this paper is to explore and evaluate the potential of combining Mixed Reality (MR) technologies with Building Information Modeling (BIM) and damage information to overcome thes...
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Veröffentlicht in: | Automation in construction 2024-12, Vol.168, p.105775, Article 105775 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Traditional bridge inspection methods have limitations, driving the need for advanced techniques. The primary objective of this paper is to explore and evaluate the potential of combining Mixed Reality (MR) technologies with Building Information Modeling (BIM) and damage information to overcome these challenges. The paper aims to improve communication, collaboration, and the accuracy of structural damage identification during inspections. Parametric objects were developed to accurately represent and locate damage within the BIM model of the Coimbra I Viaduct in Brazil, using detailed geometric parameters. On-site inspections leveraged MR technologies, enabling real-time integration of damage information into the BIM. This approach allowed full-scale interaction with the model in augmented reality (AR), facilitating direct comparison with actual structural features and improving the accuracy and efficiency of inspections. The findings demonstrate the feasibility of a simplified MR-based inspection process, offering a complementary method within a multi-platform Bridge Management System, thereby enhancing bridge maintenance.
•MR inspection integration with a BIM model is feasible with current technology.•Parametric data structures were proposed to exchange information on damage.•Potential for a streamlined and cost-effective MR-based inspection routine.•Effectiveness depends on ongoing advancements in establishing a BIM-based BMS.•Budget-limited agencies face challenges in modeling extensive bridge networks. |
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ISSN: | 0926-5805 |
DOI: | 10.1016/j.autcon.2024.105775 |