中国民航大学学报 ›› 2019, Vol. 37 ›› Issue (6): 12-17.

• 民用航空 • 上一篇    下一篇

航空发动机基线挖掘方法对比分析

曹惠玲,徐文迪,汤鑫豪,崔科璐,王冉   

  1. (中国民航大学航空工程学院,天津300300)
  • 收稿日期:2018-06-08 修回日期:2018-09-05 出版日期:2019-12-31 发布日期:2019-12-31
  • 作者简介:曹惠玲(1962—),女,河北唐山人,教授,博士,研究方向为航空发动机性能分析与故障诊断.

Comparison and analysis of aero-engine baseline detection approaches

CAO Huiling, XU Wendi, TANG Xinhao, CUI Kelu, WANG Ran   

  1. (College of Aeronautical Engineering, CAUC, Tianjin 300300, China)
  • Received:2018-06-08 Revised:2018-09-05 Online:2019-12-31 Published:2019-12-31

摘要: 基线是航空发动机状态监控及故障诊断的基础,内置于国外OEM 厂家提供的各种监控系统中,是发动机状态监控和性能分析的技术壁垒。中国学者针对基线的准确定义、获取基线数据的途径及基线方程的建立方法等展开了深入而广泛的研究,给出了各种形式的基线方程。归纳汇总各种基线挖掘方法,并通过实际航班数据进行验证,分析了不同挖掘方法的优劣,为发动机监控和分析提供理论参考。

关键词: 航空发动机基线, 神经网络, 支持向量回归机, 高斯牛顿迭代法, 最小二乘法

Abstract: Baseline is the foundation for aero engine condition monitoring and fault diagnosis. It is hidden in the monitoring systems provided by OEM and is a barrier for monitoring and performance analysis of the engine by operators.Amount in-depth and extensive researches are conducted on the accurate baseline definition, the acquisition of baseline data and the establishment of baseline equations. Several baseline data mining methods are compared and var ified with actual flight data, providing theoretical a useful reference for engine monitoring and analysis.

Key words: aero-engine baseline, neural network, SVR, Gauss-Newton interative method, least square method

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