摘要
针对国产涡轴发动机批产过程中整机性能分散性问题,提出了一种结合制造几何参数、部件性能、整机性能3个维度的模型建立方法。首先,调研获取了200台新机重要部件制造几何参数与出厂性能参数,通过Spearman相关系数法筛选出发动机重要部件关键制造几何参数。其次,基于发动机新机出厂性能参数和部件级模型,利用部件特性修正因子对发动机部件特性图进行修正,基于粒子群优化支持向量回归(Particle swarm optimized support vector regression,PSO-SVR)方法建立了发动机重要部件关键制造几何参数与部件特性修正因子的对应关系。最后,建立发动机重要部件关键制造几何参数-部件性能-整机性能模型。验证结果表明,模型在25%额定功率状态下整机性能预测误差不超过5%,在50%、75%、95%、100%、105%额定功率状态下整机性能预测误差不超过3%。该模型能够仿真发动机重要部件关键制造几何参数对整机性能分散性的影响,可以在发动机未试车前进行整机性能预测。
Aiming at the problem of performance dispersion of domestic turboshaft engines in batch production,a model-building method integrating manufacturing geometric parameters,component performance,and overall engine performance is proposed.Firstly,the manufacturing geometric parameters and factory performance parameters of important components from 200 new engines are obtained,and the key manufacturing geometric parameters of important engine components are screened by the Spearman correlation coefficient method.Secondly,based on the factory performance parameters of new engines and component-level models,the characteristic diagrams of important engine components are modified using component characteristic correction factors.Based on the particle swarm optimized support vector regression(PSO-SVR)method,the corresponding relationship between the key manufacturing geometric parameters of important engine components and component characteristic correction factors is established.Finally,a model of key manufacturing geometric parameters of important engine components-component performance-overall engine performance is established.The verification results show that the prediction error of the model for the overall engine performance is less than 5% at the 25% rated power,and less than 3% at 50%,75%,95%,100%,and 105% rated powers.The model can simulate the influence of key manufacturing geometric parameters on the dispersion of engine performance and enable the prediction of overall engine performance before engine testing.
作者
李泽琪
席龙
邓浩民
周文祥
孙思琦
LI Zeqi;XI Long;DENG Haomin;ZHOU Wenxiang;SUN Siqi(College of Energy and Power Engineering,Nanjing University of Aeronautics&Astronautics,Nanjing 210016,China;China Electronic Product Reliability and Environmental Testing Research Institute,Guangzhou 511370,China)
出处
《南京航空航天大学学报(自然科学版)》
北大核心
2025年第4期681-692,共12页
Journal of Nanjing University of Aeronautics & Astronautics (Natural Science Edition)
关键词
分散性
几何参数
修正因子
逆流路法
支持向量回归
涡轴发动机
dispersibility
geometric parameter
correction factor
reverse flow method
support vector regression(SVR)
turboshaft engine
作者简介
通信作者:孙思琦,女,工程师,E-mail:sunsiqi@ceprei.com。
