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基于性能数字孪生的航空发动机性能衰退实时监测与评估方法

王栋欢 金海 万东凯 王军 肖洪

航空学报2026,Vol.47Issue(5):55-69,15.
航空学报2026,Vol.47Issue(5):55-69,15.DOI:10.7527/S1000-6893.2025.32459

基于性能数字孪生的航空发动机性能衰退实时监测与评估方法

Real-time monitoring and evaluation method for aero-engine performance degradation based on performance digital twin

王栋欢 1金海 2万东凯 2王军 2肖洪3

作者信息

  • 1. 中国航发沈阳发动机研究所,沈阳 110015||西北工业大学 动力与能源学院,西安 710072
  • 2. 中国航发沈阳发动机研究所,沈阳 110015
  • 3. 西北工业大学 动力与能源学院,西安 710072
  • 折叠

摘要

Abstract

To enable real-time performance monitoring and degradation assessment of aircraft engines,a digital-twin-based methodology for real-time monitoring and evaluation of engine performance degradation is proposed.A perfor-mance digital twin architecture was designed and implemented by integrating Long Short-Term Memory(LSTM)recur-rent neural networks with the engine's physical structural configuration.Baseline models of the performance digital twin were established using flight parameter data from the initial operational flights of an engine.The model demon-strates high-fidelity simulation capabilities for replicating the engine's performance across diverse flight conditions.By feeding real-time operational parameters and flight state data into the baseline model,the real-time performance met-rics of a pristine(non-degraded)engine under current operating conditions are simulated.Comparative analysis be-tween simulated outputs and actual sensor measurements enables quantitative assessment of the engine's instanta-neous performance degradation.A case study involving 185 flight cycles validated the framework:Baseline models constructed from the first three flights achieved mean absolute relative errors below 0.98%,0.94%,and 1.89%for ro-tational speed,pressure,and temperature predictions,respectively,with single-point inference time under 0.14 milli-seconds,confirming the reliability of real-time digital twinning.The degradation assessment results of this method align well with traditional methods,demonstrating significant feasibility and advantages.

关键词

航空发动机/数字孪生/性能监测/衰退评估/LSTM/架构驱动

Key words

aero-engine/digital twin/performance monitoring/degradation assessment/LSTM/architecture-driven

分类

航空航天

引用本文复制引用

王栋欢,金海,万东凯,王军,肖洪..基于性能数字孪生的航空发动机性能衰退实时监测与评估方法[J].航空学报,2026,47(5):55-69,15.

基金项目

国家级项目 ()

省部级项目 National Level Project ()

Provincial or Ministerial Level Project ()

航空学报

1000-6893

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