Abstract
In recent years, my country has vigorously promoted bridge smart technology, but the technical integration of urban bridges is not ideal. As people continue to research and in-depth bridge smart operation and maintenance technology, more and more bridge designers combine advanced technology with bridge project engineering. Therefore, using BIM, VR and UAV technologies to implement multi-relevant bridge intelligent operation and maintenance has become an important topic for academic and industry research. The purpose of this article is to study the application of BIM+VR+UAV multi-relevant bridge intelligent operation and maintenance. This research is from the perspective of multi-related bridge operation and maintenance engineering. First, through literature research and systematic learning of BIM, VR and UAV software, using the characteristics of BIM, VR, and UAV smart technology that have complementary advantages after reasonable correlation, through the comparison of BIM, VR, and UAV. UAV’s technical theory analysis proposes a method for the simultaneous use of three technologies in multiple associations. This research fully explores the characteristics and advantages of BIM, VR, and UAV technology, application value and the content and methods of cost management theory and schedule management theory, and provide a theoretical basis for the research content. Based on summarizing the theories and application practices of BIM, VR, and UAV technology at home and abroad, this research integrates the existing BIM model software system to integrate the existing bridge construction theory with BIM, VR, and UAV technology, and proposes based on BIM’s engineering virtual construction technology framework and application process. The experimental results show that the crack width in area A detected by manual crack width detection is 1.0 mm, the crack width in area B is 0.9 mm, the crack width in area C is 1.3 mm, and the crack width in area D is 1.6 mm, which is the largest difference from the actual crack. The minimum difference is 0.24 mm, and the minimum difference is 0.4 mm, and the maximum difference between the measured value of the drone and the actual crack value is 0.01 mm, indicating that the drone is feasible and more accurate in identifying the width of bridge cracks.
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Peng, Y., Xiao, Y., Li, Z., Hu, T., Wen, J. (2022). Application of BIM+VR+UAV Multi-associated Bridge Smart Operation and Maintenance. In: J. Jansen, B., Liang, H., Ye, J. (eds) International Conference on Cognitive based Information Processing and Applications (CIPA 2021). Lecture Notes on Data Engineering and Communications Technologies, vol 84. Springer, Singapore. https://doi.org/10.1007/978-981-16-5857-0_70
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DOI: https://doi.org/10.1007/978-981-16-5857-0_70
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