陈斯迅, 李在蓉, 王禹钦, 关红亮, 高丽, 马江涛, 王雪莉. 管道数字孪生体模型的构建及应用[J]. 油气储运, 2021, 40(6): 643-650. DOI: 10.6047/j.issn.1000-8241.2021.06.006
引用本文: 陈斯迅, 李在蓉, 王禹钦, 关红亮, 高丽, 马江涛, 王雪莉. 管道数字孪生体模型的构建及应用[J]. 油气储运, 2021, 40(6): 643-650. DOI: 10.6047/j.issn.1000-8241.2021.06.006
CHEN Sixun, LI Zairong, WANG Yuqin, GUAN Hongliang, GAO Li, MA Jiangtao, WANG Xueli. Construction and application of Digital Twin model of pipeline[J]. Oil & Gas Storage and Transportation, 2021, 40(6): 643-650. DOI: 10.6047/j.issn.1000-8241.2021.06.006
Citation: CHEN Sixun, LI Zairong, WANG Yuqin, GUAN Hongliang, GAO Li, MA Jiangtao, WANG Xueli. Construction and application of Digital Twin model of pipeline[J]. Oil & Gas Storage and Transportation, 2021, 40(6): 643-650. DOI: 10.6047/j.issn.1000-8241.2021.06.006

管道数字孪生体模型的构建及应用

Construction and application of Digital Twin model of pipeline

  • 摘要: 根据智慧管网的概念和管道企业现状,提出数字孪生是实现智慧管网的基本方法和理论依据。基于数字孪生理论和数字孪生五维模型,构建了包含实体管道、虚拟管道、管道服务系统、管道孪生数据的管道数字孪生体模型,阐述了模型内涵、各元素之间关系、运行机制以及云计算、大数据、人工智能、物联网等关键技术的具体应用,重点分析了实体管道与虚拟管道之间的交互和融合,并探讨了管道数字孪生体模型在管道设计、施工、运行、维修等场景中的作用。在管道的全生命周期中应用管道数字孪生体,通过数据共享、信息可视化、智能分析等手段,优化了资源配置,增强了安全预警水平,提升了决策能力,为管道行业向信息化、智能化转型提供了支持。

     

    Abstract: According to the concept of intelligent pipeline network and the current status of pipeline enterprises, it was put forward that Digital Twin was the basic method and theoretical basis to realize the intelligent pipeline network. Thereby, based on the theory and the five-dimensional model of Digital Twin, a Digital Twin model of pipeline, including the physical pipeline, the virtual pipeline, the pipeline service system and the pipeline twin data, was constructed, and the connotation of the model, the relationship between various elements, the operation mechanism and the concrete application of key technologies such as cloud computing, big data, artificial intelligence and Internet of Things, were elaborated. In addition, the interaction and fusion between the physical and the virtual pipeline was analyzed, and the application of the pipeline Digital Twin model in the pipeline design, construction, operation, maintenance and other scenarios was discussed. By applying the Digital Twin in the full life cycle of pipeline, the resource allocation was optimized and the level of safety pre-warning was enhanced through data sharing, information visualization and intelligent analysis, with the decision-making ability improved and supports provided for the informatization and intelligent transformation of pipeline industry.

     

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