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飞机发动机的数字孪生:数据驱动方法-用于飞机发动机全生命周期劣化监测的嵌入式物理知识.pdf

上传人: 小小 编号:612371 2025-02-12 42页 1.70MB

1、Hong.Xiao()Northwestern Polytechnical University of China Digital Twin of Aircraft Engines Data-Driven Method Embedded Physical Knowledge to monitor the degradation September 2024 1.Digital Test and Digital Twin 2.Digital Test Cases of Aircraft Engine 3.Digital Altitude Test of Aircraft Engine 4.Int

2、elligent Network in Digital Twin Contents 2/42 More and more tests are conducted in digital spaces 1.Digital Test and Digital Twin 3/42 Ditigal Twin Process digital twin Product digital twin Our study More and more tests are conducted in digital spaces 1.Digital Test and Digital Twin 4/42 Data-drive

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4、rsonal point:Suitable for components,parts,and assemblies.Not suitable for complex thermodynamic system.1.Digital Test and Digital Twin Data-driven Model-driven mechanism can be embedded Method of embedding Intelligent network Simulation or mechanism model The Digital twin mode in the field of aircr

5、aft engines Data-Driven method embedded physical knowledge Embed physical knowledge in intelligent network 6/42 Cheap,efficient,and simple to implement.Big data required,Unexplainability,Beyond physical boundaries.1.Digital Test and Digital Twin Data-driven Model-driven mechanism can be embedded Met

6、hod of embedding Intelligent network Simulation or mechanism model The Digital twin mode in the field of aircraft engines Data-Driven method embedded physical knowledge Embed physical knowledge in intelligent network 7/42 MBSE:Model Based System Engineering Gas path Model Control Model Air Model Oil

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本文主要探讨了数字孪生在飞机发动机领域的应用,通过数据驱动的方法将物理知识嵌入智能网络,以监测发动机退化。文章提出了数字孪生模型,包括产品数字孪生和过程数字孪生,强调了数据驱动和模型驱动的区别。研究指出,数字孪生能够有效地监测飞机发动机的性能退化,并通过智能网络将物理机制嵌入其中。此外,文章还讨论了数字孪生中的数据及时性、网络改进、以及从地面测试到高空测试的知识转移等问题。
"数字孪生如何整合物理知识?" "如何解决数据不平衡问题?" "如何将地面测试知识转移到高空测试?"
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