基于建筑信息模型孪生深基坑性态可视化方法
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TU17;TU753

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国家自然科学基金(51174124);山东省自然科学基金(ZR2017MEE017);山东省 重点研发计划(公益类专项)(2018GSF120005)


Visualization Method of Deep Foundation Pit Digital Twin Behavior Based on Building Information Modeling
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The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    随着土地资源短缺,城市深基坑工程越来越多,采用孪生技术准确反映深基坑性态并及时进行风险评价对深基坑施工安全意义重大。创建了反映现场监测点信息的监测点族,作为测钉嵌入深基坑BIM(Building Information Modeling,建筑信息模型)模型中,使现场监测数据与相关BIM构件数据孪生,基于Revit软件,使用Visual Studio 2019二次开发了现场监测数据可视化模块,实现现场监测数据的深基坑可视化,建立了考虑条件信息熵的深基坑风险评价模型,并嵌入到现场监测数据可视化开发模块中,对孪生深基坑性态进行可视化。通过某深基坑实例,该可视化及风险评价方法可以更好更快的帮助施工人员定位危险单元以及制定相应的防控措施。

    Abstract:

    With the shortage of land resources, there are more and more urban deep foundation pit engineering. It is of great significance for the safety of deep foundation pit construction to use digital twin technology to reflect the behavior accurately and conduct risk assessment in time. In this paper, a monitoring family of points was created that reflects the information of monitoring points in construction site, which was embedded in the BIM (Building Information Modeling) model of deep foundation pit as monitoring nails, so that the on-site monitoring data can be used to establish the digital twin related to the data of BIM components. Based on the Revit software, the on-site monitoring data visualization module was re-developed by using Visual Studio 2019 to realize the visualization of deep foundation pit about on-site monitoring data. A risk assessment model of deep foundation pit considering conditional information entropy was established and embedded in the visualization development module of on-site monitoring data, which can visualize the deep foundation pit digital twin behavior. Through an instance of a deep foundation pit, the new visualization and risk assessment method can help construction workers to locate dangerous units and formulate corresponding prevention and control measures better and faster.

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樊延祥,袁长丰,袁铭徽,等. 基于建筑信息模型孪生深基坑性态可视化方法[J]. 科学技术与工程, 2022, 22(18): 7972-7980.
Fan Yanxiang, Yuan Changfeng, Yuan Minghui, et al. Visualization Method of Deep Foundation Pit Digital Twin Behavior Based on Building Information Modeling[J]. Science Technology and Engineering,2022,22(18):7972-7980.

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  • 收稿日期:2021-09-01
  • 最后修改日期:2022-03-26
  • 录用日期:2022-01-15
  • 在线发布日期: 2022-07-14
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