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作 者:杨坤 宗国仁 王伟 YANG Kun;ZONG Guoren;WANG Wei(College of Safety Science and Engineering,Civil Aviation University of China,Tianjin 300300,China;Key Laboratory for Civil Airworthiness Certification Technology,Tianjin 300300,China)
机构地区:[1]中国民航大学安全科学与工程学院,天津300300 [2]民航航空器适航审定技术重点实验室,天津300300
出 处:《海军航空大学学报》2025年第1期133-141,共9页Journal of Naval Aviation University
基 金:天津市教委科研计划(2023KJ227)。
摘 要:为了提高双轴涡扇发动机加速阶段数学模型的精确度,基于系统辨识方法,提出了一种航空发动机部件级辨识模型。该模型通过假设航空发动机的各个部件为Hammerstein系统,以预测关键参数。Hammerstein系统中的动态线性部分与静态非线性部分的参数能够有效描述航空发动机的动态特性。在此基础上,构建了扩展截尾随机逼近算法,并证明了其非参数递推强一致收敛性。文章对航空发动机从地面慢车到最大推力的加速过程进行了仿真模拟,并将辨识模型预测的数据与发动机实际运行数据进行了对比分析。结果显示,部件级辨识模型能够准确构建航空发动机的数学模型,并有效描述各部件的动态特性。该模型对发动机关键参数的辨识结果与实际数据的均方根误差(RMSE)均低于1%。To enhance the accuracy of the mathematical model for the acceleration phase of a dual-shaft turbofan engine,a component-level identification model for aerospace engines is proposed based on system identification methods.This model assumes that the various components of the aerospace engine are represented as Hammerstein systems to predict key parameters.The parameters of the dynamic linear and static nonlinear parts of the Hammerstein system effectively describe the dynamic characteristics of the aerospace engine.Building on this,an extended truncated random approximation algorithm is developed,and its nonparametric recursive strong consistency convergence is demonstrated.The acceleration process of the aerospace engine from idle on the ground to maximum thrust is simulated,and the data predicted by the identification model with actual operational data of the engine is compared.The results indicate that the component-level identification model can accurately construct the mathematical model of the aerospace engine and effectively describe the dynamic characteristics of its components.The root mean square error(RMSE)of the identified key parameters of the engine compared to the actual data is below 1%.
关 键 词:航空发动机建模 系统辨识 HAMMERSTEIN系统
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