从零开始！数字孪生体的几个概念详述
“ 人们为了能够思考和交流，而创造出来很多概念。
我们也是靠理解各种概念，去理解这个世界的。
永远都是那些能把“概念理解透彻、区分清楚”的人，才能清楚的思考，进而才能改变世界。”
本文关于数字孪生体概念定义的内容来源自Dr. Michael Grieves and John Vickers的文章《Digital Twin:Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems (Excerpt)》（文末有获得word版文章的办法），微 信 公 众 号“工业4.0研究院”的对该文章的翻译名家之作 | 数字孪生体概念的起源。
What would be helpful are some definitions to rely on when referring to the Digital Twin and its different manifestations. We would propose the following as visualized in Figure。
当提到数字孪生体和它的不同表现形式时，一些定义是对理解有帮助的。我们提出了一个图示，以展示其中的想法。
01
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DT，Digital Twin 数字孪生体
Digital Twin (DT) - the Digital Twin is a set of virtual information constructs that fully describes a potential or actual physical manufactured product from the micro atomic level to the macro geometrical level.
数字孪生体是一组虚拟信息结构，可以从微观原子级别到宏观几何级别全面地描述潜在或实际的物理制成品。
At its optimum, any information that could be obtained from inspecting a physical manufactured product can be obtained from its Digital Twin.
在最佳状态下，可以通过数字孪生体获得物理制成品的任何信息。
Digital Twins are oftwo types: Digital Twin Prototype (DTP) and Digital Twin Instance (DTI).
数字孪生体有两种类型：数字孪生原型（DTP）和数字孪生实例（DTI）。
DT’s are operated onin a Digital Twin Environment (DTE).
而数字孪生环境（DTE）则是数字孪生体的操作环境。
02
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DTP，Digital Twin Prototype 数字孪生体原型
Digital Twin Prototype(DTP) - this type of Digital Twin describes the prototypical physical artifact.
这种类型的数字孪生体描述了原型物理工件。
It contains the informational sets necessary to describe and produce a physicalversion that duplicates or twins the virtual version.
它包含了描述和生成一个物理产品所必需的信息集，以便物理版本与虚拟版本重合或成对。
These informational setsinclude, but are not limited to, Requirements, Fully annotated 3D model, Billof Materials (with material specifications), Bill of Processes, Bill ofServices, and Bill of Disposal.
这些信息集包括（但不仅限于）需求信息、完全注释的3D模型、材料清单（附有材料规范）、流程清单、服务清单和报废处置清单。
03
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DTI，Digital Twin Instance 数字孪生体实例
Digital Twin Instance(DTI) - this type of Digital Twin describes a specific corresponding physicalproduct that an individual Digital Twin remains linked to throughout the lifeof that physical product.
这种类型的数字孪生体描述了一个特定的、对应的物理产品，在该物理产品的整个生命周期中都有一个单独的数字孪生体与之保持连接。
Depending on the use cases required for it, this typeof Digital Twin may contain, but again is not limited to, the followinginformation sets:
根据其使用情况，这种类型的数字孪生设备可能包含但不限于以下信息集：
A fully annotated 3D model with General Dimensioning andTolerances (GD&T) that describes the geometry of the physical instance andits components;
带有通用尺寸标注和公差（GD&T）的完全注释3D模型——用于描述该物理实例及其组件的几何结构；
a Bill of Materials that lists current components and all pastcomponents;
材料清单——列出当前组件和所有过去组件；
a Bill of Process that lists the operations that were performed increating this physical instance, along with the results of any measurements andtests on the instance;
流程清单——列出创建该物理实例时执行的操作，以及对该实例进行测量和测试的所有结果；
a Service Record that describes past services performedand components replaced;
流程清单——列出创建该物理实例时执行的操作，以及对该实例进行测量和测试的所有结果；
and Operational States .
运行状态记录——从实际传感器捕获的全部运行数据，包括过去和当前的状态，以及从中推导的未来预测信息。
04
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DTA，Digital Twin Aggregate 数字孪生体原型
Digital Twin Aggregate (DTA) – this type of Digital Twin is the aggregation of all the DTIs.
这种类型的数字孪生体是所有数字孪生实例（DTI）的聚合体。
Unlike the DTI, the DTA may not be an independent data structure. It may be a computing construct that has access to all DTIs and queries them either ad-hoc or proactively.
它与DTI有所不同的是，DTA可能不是一个独立的数据结构体。它可能是一个计算结构，既可以访问所有的DTI，也可以对它们进行即时或主动的查询。
On an ad hoc basis, the computing construct might ask, “What is the Mean Time Between Failure (MTBF) of component X.”
在特定的基础上，计算结构可能会询问：“组件X的平均故障间隔时间（MTBF）是多少？”
Proactively, the DTA might continually examine sensor readings and correlate those sensor readings with failures to enable prognostics.
数字孪生聚合体可能会前瞻地持续主动检查传感器读数，并与故障关联起来实现预测。
05
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DTE，Digital Twin Environment 数字孪生体环境
Digital Twin Environment (DTE)- this is an integrated, multi-domain physics application space for operating on Digital Twins for a variety of purposes. These purposes would include:
这是一个集成的、多领域的物理应用空间，用于操作各种用途的数字孪生体。这些操作目的包括：
Predictive 预测：
the Digital Twin would be used for predicting future behavior and performance of the physical product.
数字孪生体将用于预测物理产品的未来行为和性能。
At the Prototype stage, the prediction would be of the behavior of the designed product with components that vary between its high and low tolerances in order to ascertain that the as-designed product met the proposed requirements.
在原型阶段可以预测某个产品设计的性能及其组件在高容差和低容差之间的变化，以确定该设计是否满足所提出的要求。
In the Instance stage, the prediction would be a specific instance of a specific physical product that incorporated actual components and component history.
在实例阶段预测将是包含了组件及其历史的特定物理产品的特定实例。
The predictive performance would be based from current point in the product's lifecycle at its current state and move forward. Multiple instances of the product could be aggregated to provide a range of possible future states.
预测性能将基于产品生命周期中当前状态下的实时情况并向前推进，可以聚合产品的多个实例，以提供一系列可能的未来状态。
Interrogative 查询
this would apply to DTI’s as the realization of the DTA.
这适用于数字孪生实例作为数字孪生聚合体的实现。
Digital Twin Instances could be interrogated for the current and past histories.
数字孪生实例可以询问当前和过去的历史信息。
Irrespective of where their physical counterpart resided in the world, individual instances could be interrogated for their current system state: fuel amount, throttle settings, geographical location, structure stress, or any other characteristic that was instrumented.
无论它们的物理对应物在世界上什么地方，都可以查询其当前的系统状态：燃料量、节流阀设置、地理位置、结构应力，或任何已检测的其它特征。
Multiple instances of products would provide data that would be correlated for predicting future states.
产品多个实例将提供相关数据以预测未来状态。
For example, correlating component sensor readings with subsequent failures of that component would result in an alert of possible component failure being generated when that sensor pattern was reported. The aggregate of actual failures could provide Bayesian probabilities for predictive uses.
例如，将组件的传感器读数与该组件的后续故障相关联，可以在报告该传感器的模式时生成故障警报，预测有可能发生的组件故障。而实际发生的故障集 合可以为预测用途提供贝叶斯概率分析。
