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数字孪生仿真 — 混合虚拟副本

数字孪生仿真(Digital Twin Simulation)最早由迈克尔·格里夫斯(Michael Grieves)于2002年左右在密歇根大学提出概念,并于2014年正式在其白皮书中进行了描述。它通过将实时传感器数据与机械(基于物理)模型和机器学习组件融合,创建一个物理系统的持续更新的虚拟副本。该孪生模型能够反映物理资产的当前状态并预测其未来行为,从而能够在不干扰真实系统的情况下实现故障检测、预测性维护和运行优化。

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来源

  1. Grieves, M. (2014). Digital Twin: Manufacturing Excellence through Virtual Factory Replication. White Paper, University of Michigan. link
  2. Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H. & Sui, F. (2018). Digital Twin-Driven Product Design, Manufacturing and Service with Big Data. The International Journal of Advanced Manufacturing Technology, 94, 3563-3576. DOI: 10.1007/s00170-017-0233-1

如何引用本页

ScholarGate. (2026, June 1). Digital Twin Simulation (Hybrid Physics-ML Virtual Replica). ScholarGate. https://scholargate.app/zh/simulation/digital-twin-simulation

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ScholarGateDigital Twin Simulation (Digital Twin Simulation (Hybrid Physics-ML Virtual Replica)). 于 2026-06-15 检索自 https://scholargate.app/zh/simulation/digital-twin-simulation · 数据集: https://doi.org/10.5281/zenodo.20539026