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Volume 52 Issue 2
Feb.  2022
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Article Contents
JIANG Zhenyu, XIE Huibing. Research on Integration of Detection and Analysis for Rigid-Frame Bridges Based on BIM[J]. INDUSTRIAL CONSTRUCTION, 2022, 52(2): 180-185. doi: 10.13204/j.gyjzG21041612
Citation: JIANG Zhenyu, XIE Huibing. Research on Integration of Detection and Analysis for Rigid-Frame Bridges Based on BIM[J]. INDUSTRIAL CONSTRUCTION, 2022, 52(2): 180-185. doi: 10.13204/j.gyjzG21041612

Research on Integration of Detection and Analysis for Rigid-Frame Bridges Based on BIM

doi: 10.13204/j.gyjzG21041612
  • Received Date: 2021-04-16
    Available Online: 2022-06-30
  • Publish Date: 2022-02-20
  • Bridge informatization methods based on BIM have been more and more widely used in the process of bridge construction and operation management. In order to solve the problems of unintuitive and unjustified disease analysis caused by the deficiency in disease location, type, and information data collected during the detection process, and to provide new innovative ideas for bridge detection technology, a rigid frame bridge was taken as an example, a method was proposed to achieve disease severity classification analysis and disease management based on BIM technology. A model considering the structural ontology model and the rehabilitation model was established, the automatic generation of cracks and disease information and the addition of attribute information could be realized, so as to achieve further analysis of crack direction, the time distribution of diseases, and the crack distribution along the longitudinal bridge segments direction, and output tables and charts to visually express the statistical analysis results. The BIM model data of the concerned part was extracted and imported into ABAQUS for solid finite element analysis. The calculation results were consistent with the preliminary analysis conclusions. At the same time, the calculated results were correlated with the BIM model in the form of parameters, table mapping, and hyperlinks to realize the integration of multi-source data.
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