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Volume 56 Issue 3
Jun.  2021
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Journal of Southwest Jiaotong University  > 2021  >  56(3): 461-468, 492.
WEI Xing, ZOU Jianhao, XIAO Lin, CHEN Yang, GU Xingyu. Digital Management of Crack Defects Information in Steel Truss Bridges Based on Building Information Modeling[J]. Journal of Southwest Jiaotong University, 2021, 56(3): 461-468, 492. doi: 10.3969/j.issn.0258-2724.20190507
Citation: WEI Xing, ZOU Jianhao, XIAO Lin, CHEN Yang, GU Xingyu. Digital Management of Crack Defects Information in Steel Truss Bridges Based on Building Information Modeling[J]. Journal of Southwest Jiaotong University, 2021, 56(3): 461-468, 492. doi: 10.3969/j.issn.0258-2724.20190507
shu

Digital Management of Crack Defects Information in Steel Truss Bridges Based on Building Information Modeling

doi: 10.3969/j.issn.0258-2724.20190507
  • Received Date: 02 Jun 2019
  • Rev Recd Date: 01 Oct 2019
    • Available Online: 23 Oct 2019
  • Publish Date: 15 Jun 2021
    Abstract
  • In order to solve the problem of complex data collection process, poor visualization effect and lack of time-related factors in the traditional bridge defects information management process, the building information modeling (BIM) technology was used to realize the visualization of a steel truss bridge crack defect, and a method for rapid batch update of crack defects information was developed with the visual programming software Dynamo, in which the update code is modularized. By introducing time parameters of defects, a 4D crack defects information model was created, whereby the dynamic correlation between crack defect information and 3D graphics in time series was realized, and the crack propagation law was presented. Results show that the introduction of BIM technology into the bridge defects management system can improve the efficiency of defects information management and realize the visualization of crack defects information. The created 4D crack defects information model can intuitively present the development process of crack defects, facilitate bridge operation and maintenance, and help managers scientifically predict the trend of crack development.

     

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