Digital twin data: methods and key technologies

Digital Twin Pub Date : 2021-09-22 DOI:10.12688/digitaltwin.17467.1

Meng Zhang, F. Tao, Biqing Huang, Ang Liu, Lihui Wang, N. Anwer, A. Nee

引用次数: 23

Abstract

As a promising technology to converge the traditional industry with the digital economy, digital twin (DT) is being investigated by researchers and practitioners across many different fields. The importance of data to DT cannot be overstated. Data plays critical roles in constructing virtual models, building cyber-physical connections, and executing intelligent operations. The unique characteristics of DT put forward a set of new requirements on data. Against this background, this paper discusses the emerging requirements on DT-related data with respect to data gathering, mining, fusion, interaction, iterative optimization, universality, and on-demand usage. A new notion, namely digital twin data (DTD), is introduced. This paper explores some basic principles and methods for DTD gathering, storage, interaction, association, fusion, evolution and servitization, as well as the key enabling technologies. Based on the theoretical underpinning provided in this paper, it is expected that more DT researchers and practitioners can incorporate DTD into their DT development process.

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数字孪生数据:方法与关键技术

数字孪生技术(digital twin, DT)作为一项将传统产业与数字经济融合的技术，正受到许多不同领域的研究人员和实践者的研究。数据对DT的重要性怎么强调都不为过。数据在构建虚拟模型、建立网络物理连接和执行智能操作中起着至关重要的作用。DT的独特特性对数据提出了一系列新的要求。在此背景下，本文讨论了在数据收集、挖掘、融合、交互、迭代优化、通用性和按需使用等方面对dt相关数据的新需求。提出了数字孪生数据(DTD)的概念。本文探讨了DTD的收集、存储、交互、关联、融合、演化和服务化的基本原理和方法，以及关键的使能技术。基于本文提供的理论基础，期望更多的DT研究者和实践者能够将DTD纳入到他们的DT开发过程中。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Digital Twin digital twin technologies-

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期刊介绍： Digital Twin is a rapid multidisciplinary open access publishing platform for state-of-the-art, basic, scientific and applied research on digital twin technologies. Digital Twin covers all areas related digital twin technologies, including broad fields such as smart manufacturing, civil and industrial engineering, healthcare, agriculture, and many others. The platform is open to submissions from researchers, practitioners and experts, and all articles will benefit from open peer review.  The aim of Digital Twin is to advance the state-of-the-art in digital twin research and encourage innovation by highlighting efficient, robust and sustainable multidisciplinary applications across a variety of fields. Challenges can be addressed using theoretical, methodological, and technological approaches. The scope of Digital Twin includes, but is not limited to, the following areas:  ● Digital twin concepts, architecture, and frameworks ● Digital twin theory and method ● Digital twin key technologies and tools ● Digital twin applications and case studies ● Digital twin implementation ● Digital twin services ● Digital twin security ● Digital twin standards Digital twin also focuses on applications within and across broad sectors including: ● Smart manufacturing ● Aviation and aerospace ● Smart cities and construction ● Healthcare and medicine ● Robotics ● Shipping, vehicles and railways ● Industrial engineering and engineering management ● Agriculture ● Mining ● Power, energy and environment Digital Twin features a range of article types including research articles, case studies, method articles, study protocols, software tools, systematic reviews, data notes, brief reports, and opinion articles.