Abstract: The tip clearance distribution of multistage rotor and stator is an important index to measure the assembly quality of aero engines,and the traditional assembly methods are difficult to accurately predict and control assembly clearance.In view of the above problems,a dynamic prediction and control method of assembly clearance of MRS driven by digital twin was proposed.On the basis of analyzing the assembly process,a digital twin model for assembly clearance control of multistage rotor and stator was established,which focused on time variation.Through the measured data driven service model,online prediction of assembly clearance and dynamic regulation of assembly process were realized.The twin data types and the fusion iterative process were sorted out.Four service models were built to realize data fusion iteration.The effectiveness of the proposed method was verified by the assembly process of a compressor.The evolution characteristics of the rotor stator assembly's digital twin model in the time dimension provided a basis for realizing the online prediction and dynamic regulation of multistage rotor stator assembly clearance.

Key words: digital twin, multistage rotor and stator assembly, assembly clearance, assembly prediction, process optimization

摘要： 多级转静子装配间隙是影响航空发动机性能和安全的重要因素,传统装配方法难以精确预测和精准控制装配间隙,针对该问题,提出一种数字孪生驱动的转静子装配间隙动态预测与调控方法。在分析转静子装配工艺的基础上,建立了重点体现时变性的转静子装配间隙控制数字孪生模型,通过实测数据驱动服务模型实现装配间隙在线预测和装配工艺动态调控,研究了孪生数据类型与融合迭代过程,构建了实现数据融合迭代的4类服务模型,并通过某压气机装配验证了该方法的可行性与有效性;所表征的转静子装配数字孪生模型在时间维度的演化特性,为实现转静子装配间隙的在线预测与动态调控提供了基础。

关键词: 数字孪生, 多级转静子装配, 装配间隙, 装配预测, 工艺优化