针对风电项目工程规模大、工区分散、工期紧等难点与特点,提出以工程建设管控内容为物理对象（PE）、以BIM虚拟模型为孪生载体（VE）、以双向孪生数据为核心（DD）、以协同管控为目标（WM）、以协同运行规则（RU）为驱动的风电项目建设智能四维协同数字孪生模型,利用GPS-RTK+UWB无缝耦合定位技术结合自主研发的物联感知装备实现建设信息全方位智能感知,以GIS模型为数据空间集成底板,以BIM模型为数据业务集成底板形成具备交互分析特征的数字孪生载体,通过对类似及目标工程建设数据的深度学习,按过程结合综合评定体系实现建设项目的管控协同评判。通过在腊巴山风电建设项目的应用,证明该技术可实现对工程高精度、秒级的实时感知,提供轻量化、可供分析、虚实融合的孪生载体,并能根据建设环境动态调整评判参数,较准确地对风电工程建设情况进行评判,为各方协同管理提供技术支持。
Abstract
Aiming at the difficulties and characteristics of wind power projects, such as large project scale, dispersed work areas, and short timelines, an intelligent 4-dimensional collaborative digital twin model of wind power project construction is proposed, with engineering construction control content as the physical object （PE）, BIM virtual model as the twin carrier （VE）, bidirectional twin data as the core （DD）, collaborative control as the goal （WM）, and collaborative operation rules（RU） as the driver. The model uses GPS-RTK+UWB seamless coupling positioning technology in conjunction with self-developed IOT perception equipment to realize all-round intelligent perception of construction information, takes GIS model as data space integration base plate, takes BIM model as data business integration base plate to form a digital twin carrier with interactive analysis characteristics. Through deep learning of similar and target project construction data, the management and control collaborative evaluation of construction projects is realized according to the process and comprehensive evaluation system.Through the application in the Labashan wind power construction project, it is proved that the technology can realize the real-time perception of the high precision and second level of the project, provide the twin carrier of lightweight, available for analysis, virtual and real fusion, and can dynamically adjust the evaluation parameters according to the construction environment, more accurately judge the wind power project construction situation, and provide technical support for collaborative management of all parties.
关键词
数字孪生 /
深度学习 /
风电建设 /
协同管控 /
工作分解结构 /
BIM
Key words
digital twin /
deep learning /
wind powe construction /
collaborative control /
work breakdown structure /
BIM
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