数字孪生可以实现物理空间与数字空间之间的映射和交互，在工业领域展现出巨大的发展前景。针对天然气脱水性能参数检测效率低和气站工艺参数无法在线优化的问题，将数字孪生应用于化工行业，构建了三甘醇（triethylene glycol, TEG）脱水装置数字孪生系统的整体框架。结合物理设备建立了孪生系统的几何模型，并基于物理数据实时驱动建立了脱水系统工艺流程模型，最后，通过虚实映射模型完成物理空间和数字空间的映射，最终建立脱水装置的孪生模型。该模型可实现物理设备与虚拟设备的并行运行。通过提出的数字孪生系统，能够实现对天然气水露点等脱水性能参数的实时预测；以低能耗为目标，通过孪生模型中的优化算法，可实现对脱水工艺参数的在线优化，提升经济效益。

The digital twin concept completes the mapping and interaction between physical space and digital space, showing great potential for development in the industrial field. With considering the low detection efficiency of natural gas dehydration performance parameters and the inability to optimize gas station process parameters online, this paper applies the digital twin concept in the chemical industry to establish an overall framework of the digital twin system for triethylene glycol(TEG) dehydration. On one hand, the geometric model of the twin system is constructed by integrating physical devices. On the other hand, the flow model dehydration system technology is established based on the real-time driving of physical data. Finally, the twin model of dehydration is established by designing virtual-real mapping model, completing the mapping of physical space and digital space, which enables the parallel operation of the physical device and the virtual device. Through the proposed digital twin system, real-time prediction of natural gas water dew point and other dehydration performance parameters can be achieved. To achieve the goal of low power consumption, the optimization of dehydration process parameters is realized by combining optimization algorithms with the twin model, thereby improving economic efficiency.

TP302.1

国家自然科学基金资助项目（52275518）。