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基于数字孪生的设备管网爆管判定技术研究

Digital twin-based pipe burst detection technology for equipment pipe networks

  • 摘要: 为提升隐蔽环境下消防、暖通、给排水等设备管网爆管事件的自动识别、快速定位能力及管网分布全域管控水平,文章采用三维建模与数字孪生技术,构建基于 D-S(Dempster-Shafer)证据理论的设备管网数字孪生判定模型。通过生成多批次爆管模拟数据,完成对爆管推理算法的有效性验证。针对现场作业人员终端设备三维模型渲染硬件性能不足的现状,提出一种三维模型渲染轻量化优化方案。设计并实现了验证实验,实验结果表明,所建模型对设备管网爆管事件的识别准确率可达 95% 以上,模型渲染效率得到显著提升,具备良好的工程应用与推广价值。

     

    Abstract: To improve the capabilities of automatic identification and rapid location of pipe burst accidents for the equipment pipe networks of fire protection, Heating, Ventilation and Air Conditioning (HVAC), water supply and drainage in concealed environments, as well as the overall management level of pipeline distribution, this paper adopted 3D modeling and digital twin technology, and constructed a digital twin detection model for equipment pipe networks based on the Dempster-Shafer (D-S) evidence theory. It generated multiple batches of simulated pipe burst data and completed the effectiveness verification of the pipe burst inference algorithm. Considering the insufficient hardware performance of on-site operators’ terminal devices in rendering 3D models, the paper proposed a lightweight optimization scheme for 3D model rendering. It designed and carried out verification experiments. The experimental results show that the identification accuracy of the proposed model for pipe bursts of equipment pipe networks exceeds 95%, and the model rendering efficiency is significantly improved. The proposed model possesses good engineering application and promotion value.

     

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