航空发动机数字孪生专栏

数字孪生驱动的航空发动机转子精密堆叠装配

  • 王泽生 ,
  • 王辉 ,
  • 张鹏飞 ,
  • 杜立峰 ,
  • 包宏强 ,
  • 林东
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  • 1.清华大学 机械工程系,北京 100084
    2.北京航空航天大学 航空发动机研究院,北京 100191
    3.中国航发沈阳黎明航空发动机有限责任公司,沈阳 110043
.E-mail: wanghuisx@buaa.edu.cn

收稿日期: 2023-10-24

  修回日期: 2023-11-17

  录用日期: 2024-01-10

  网络出版日期: 2024-03-11

基金资助

国家科技重大专项(J2022-VII-0001-0043)

Precision stacking assembly of aero-engine rotor driven by digital twin

  • Zesheng WANG ,
  • Hui WANG ,
  • Pengfei ZHANG ,
  • Lifeng DU ,
  • Hongqiang BAO ,
  • Dong LIN
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  • 1.Department of Mechanical Engineering,Tsinghua University,Beijing 100084,China
    2.Research Institute of Aero-engine,Beihang University,Beijing 100191,China
    3.AECC Shenyang Liming Aero-Engine Co. ,Ltd. ,Shenyang 110043,China

Received date: 2023-10-24

  Revised date: 2023-11-17

  Accepted date: 2024-01-10

  Online published: 2024-03-11

Supported by

National Science and Technology Major Project of China(J2022-VII-0001-0043)

摘要

航空发动机极高的结构复杂度和高性能、高稳定性的严格要求对航空发动机制造技术提出了挑战。装配是控制航空发动机产品质量的关键制造环节,其中,转子作为航空发动机的核心动力部件,其装配精度和质量极大地影响着航空发动机的使用性能。转子由多级零件串联装配而成,装配过程中零件误差积累和传递、连接结构挤压变形等因素都容易导致装配偏差产生。针对航空发动机转子装配偏差问题,开展了数字孪生驱动的装配工艺优化方法研究。结合数字孪生方法展开装配工艺机理分析,从转子装配单元数字孪生总体技术框架、装配工艺数字化内核分析、装配工艺综合评价与决策方法三方面开展数字孪生装配优化技术研究,融合多物理因素分析模型建立装配工艺数字化分析模型,实现了数据驱动的转子装配过程监控和工艺优化分析。通过转子装配实验应用验证,所提出优化方法给出的优化装配结果与最大可能偏差相比降低了57.4%,证明所提出的数字孪生转子装配优化方法能够有效解决实际问题,为航空发动机转子装配质量预测和优化提供了新的途径。

本文引用格式

王泽生 , 王辉 , 张鹏飞 , 杜立峰 , 包宏强 , 林东 . 数字孪生驱动的航空发动机转子精密堆叠装配[J]. 航空学报, 2024 , 45(21) : 629759 -629759 . DOI: 10.7527/S1000-6893.2024.29759

Abstract

The extremely high structural complexity of the aero-engine, together with its strict requirements of high performance and stability pose big challenges to aero-engine manufacturing technology. Assembly is a key procedure of aero-engine manufacturing that directly affects product quality, wherein rotor is the key power component of aero-engine, in that its assembly accuracy and quality have great influence on aero-engine performance. Rotor is assembled by multiple parts in series, and the assembly error can be arisen by such multiple factors as error accumulation and connection structure deformation. Aiming at the issue of aero-engine rotor assembly error, a data-driven assembly error optimization method is studied. The mechanism of assembly process is analyzed combining the digital twin technology. Research is carried on digital twin assembly optimization technology from three aspects, including the overall technical framework of rotor assembly unit digital twin, digital analysis model of assembly process, and comprehensive evaluation and decision methods of assembly process. A digital analysis model for assembly process is proposed integrating analysis models of multi physical factors. Then data-driven rotor assembly process monitoring and process optimization can be realized. Through application verification of rotor assembly, the proposed optimization method reduces the assembly error by 57.4% compared to the maximum possible error. The digital twin driven rotor assembly optimization method is then proved to be effective for practical problems, providing a new approach for solving the quality prediction and optimization problems of aero-engine rotor assembly.

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