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Crane Lifting Optimization and Construction Monitoring in Steel Bridge Construction Project Based on BIM and UAV
Author(s) -
Jiahao Tian,
Sang Luo,
Xinming Wang,
Jing Hu,
Jun Yin
Publication year - 2021
Publication title -
advances in civil engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.379
H-Index - 25
eISSN - 1687-8094
pISSN - 1687-8086
DOI - 10.1155/2021/5512229
Subject(s) - bridge (graph theory) , modular design , building information modeling , process (computing) , engineering , collision detection , construction engineering , computer science , civil engineering , collision , medicine , compatibility (geochemistry) , chemical engineering , operating system , computer security
Modular construction methods are adopted in many spatial and temporal limited projects. As the major equipment used in modular construction, the mobile crane affects the safety and efficiency of construction significantly. Currently, building information modeling (BIM) is widely adopted to improve the lifting operation planning of cranes. However, the inaccurate simulation of the dynamic construction environment makes those BIM-based lifting operation planning methods unsuitable for land mobile cranes operation planning, such as in the overpass bridge construction project, which may cause several safety risks during the lifting process. Based on an overpass steel bridge construction project, this paper attempted to integrate the BIM and unmanned aerial vehicles (UAVs) to streamline lifting operation planning and construction monitoring. Specifically, in the preliminary stage, a level of development (LOD) 400 steel superstructure model was built and then divided into eighty sections. In addition, a three-dimensional (3D) geology model of the as-is construction site was modeled by UAV-captured images. Then, a fusion model which contains the lifting modules models, the as-is site model, and the crane model was gathered, based on which the collision detection was conducted by 4D crane operating path simulation. According to the results, three potential collisions were found and eliminated by lengthening the jib of the crane from 43.5 m to 46.5 m. Furthermore, the optimum crane location for lifting each steel structure was determined based on the 3D geology model. The study shows that the UAV is able to acquire geological information and then 3D simulates the real construction environment quickly and accurately. Furthermore, BIM and UAV have the potential to optimize the design and construction as well as the monitoring of bridge projects.

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