Data: A Design Framework for Adaptive Digital Twins

This paper develops a new DT design framework that uses ontologies to enable co-evolution with the CES by capturing data in terms of variety, velocity, and volume across the asset life-cycle. The framework has been tested successfully on a helicopter gearbox demonstrator and a mobile robotic system across their life cycles, illustrating DT adaptiveness without the data architecture needing to be modified. The data presented in this portal is related to the data that was generated in the validation process.

本文提出一种新型数字孪生（Digital Twin, DT）设计框架，该框架借助本体（ontology）技术，通过采集资产全生命周期内具备多样性、速度与体量特征的数据，实现与CES的协同演化。该框架已在直升机变速箱演示平台与移动机器人系统的全生命周期场景中完成验证测试，验证了数字孪生无需修改数据架构即可实现自适应演化的特性。本门户所展示的数据，均与该框架验证过程中生成的数据集相关。