基于风扇退化的涡扇发动机寿命衰减双参数评估方法研究  

A Two-Parameter Evaluation Method of Turbofan Engine Life Decay Based on Fan Degradation

作　　者：郭庆[1] 李印龙 张渝舜 GUO Qing;LI Yin-long;ZHANG Yu-shun(College of Aeronautical Engineering,Civil Aviation University of China,Tianjin 300300,China)

机构地区：[1]中国民航大学航空工程学院,天津300300

出　　处：《推进技术》2023年第7期225-233,共9页Journal of Propulsion Technology

基　　金：中国民航大学研究生科技创新基金(2020YJS014);南京航空航天大学中央高校基本科研业务费(NJ2022021)。

摘　　要：由于涡扇发动机不同单元体之间存在耦合性,采用单一性能退化参数预测发动机剩余寿命明显是不全面的。本文根据风扇故障导致涡扇发动机退化机理,引入Frank Copula函数描述二元性能参数之间的相关性,并且采用二元非线性Wiener过程来构建性能退化模型,然后基于MCMC(Markov Chain Monte Carlo)方法进行模型参数估计,实现涡扇发动机剩余寿命预测。最终,通过涡扇发动机的仿真数据集来验证该方法的适用性。证明基于Copula函数的二元非线性Wiener过程建模为发动机剩余寿命预测提供了理论基础和技术支持。Due to the coupling between different units of turbofan engines,it is obvious that the use of a sin⁃gle performance degradation parameter to predict the remaining engine life is not comprehensive.Based on the degradation mechanism of turbofan engine caused by fan failure,Frank Copula function is introduced to describe the correlation between binary performance parameters,and a binary nonlinear Wiener process is used to con⁃struct a performance degradation model,and then the model parameters are estimated based on MCMC(Markov Chain Monte Carlo)method to achieve the remaining life prediction of turbofan engine.Finally,the applicability of the method is verified by the simulation data set of turbofan engine.It is demonstrated that the binary nonlinear Wiener process modelling based on Copula function provides the theoretical basis and technical support for the re⁃maining engine life prediction.

关 键 词：涡扇发动机 相关失效 COPULA函数 二元非线性Wiener MCMC方法 

分 类 号：V267[航空宇航科学与技术—航空宇航制造工程]