基于相似理论的航空发动机风扇转速换算方法的改进

夏存江; 王聃

doi:10.13224/j.cnki.jasp.2016.04.022

基于相似理论的航空发动机风扇转速换算方法的改进

doi: 10.13224/j.cnki.jasp.2016.04.022

夏存江¹,
王聃²

1. 中国民用航空飞行学院航空发动机维修培训中心, 四川广汉 618307;
2. 中国民用航空飞行学院航空工程学院, 四川广汉 618307

基金项目:

国家自然科学基金(51306201)

详细信息

作者简介:
夏存江(1971-),男,四川仪陇人,副教授、硕士生导师,硕士,主要从事航空发动机维修技术的研究.

中图分类号: V263.4⁺7;TP311.132.4
计量
- 文章访问数: 1281
- HTML浏览量: 90
- PDF量: 546
- 被引次数: 0
出版历程
- 收稿日期: 2015-07-14
- 刊出日期: 2016-04-28

Improved correction methods of aircraft engine fan speed based on similarity theory

XIA Cun-jiang¹,
WANG Dan²

1. Aero Engine Maintenance Training Center, Civil Aviation Flight University of China, Guanghan Sichuan 618307, China;
2. Aviation Engineering Institute, Civil Aviation Flight University of China, Guanghan Sichuan 618307, China

摘要

摘要: 基于相似理论提出一种通过变指数因子计算航空发动机风扇换算转速的改进方法.收集不同公司的某型航空发动机的巡航数据建立数据样本.采用支持向量回归机方法建立指数因子与大气温度的数学模型并利用遗传算法对模型参数进行寻优,进而得到由风扇指示转速和大气温度计算风扇换算转速的变指数因子模型.使用该模型对样本数据进行计算,并把结果与定指数因子方法求解的风扇换算转速进行对比,对改进算法与定指数法换算结果进行了误差分析.结果表明:改进后的变指数因子模型计算的航空发动机风扇换算转速具有更高的精度,同时具有良好的推广泛化性能,该方法是航空发动机风扇换算转速的一种有效算法,在航空发动机性能预测也具有实际的指导意义.
- 航空发动机 /
- 风扇转速换算 /
- 相似理论 /
- 支持向量回归机 /
- 遗传算法 /
- 变指数因子
Abstract: One improved correction method of aircraft engines fan speed by variable index factor was proposed based on the similarity theory. The cruise data of an aircraft engine from different airlines were collected to build the data sample. Method of support vector regression machine was used to establish the model of index factor and atmosphere temperature, and the model parameters were optimized based on genetic algorithm. The variable index factor model, consisting of indicated fan speed and atmosphere temperature, was set up to calculate the corrected fan speed. The model was applied by sample data, and the results were compared with those by fixed index factor method, then the error analysis was drawn through the calculation results of two methods. The result indicates that aircraft engine corrected fan speed has higher accuracy through the method of variable index factor and the model has good generalization performance, so it is an effective approach for computing aircraft engine corrected fan speed, providing a practical guidance for the aircraft engine performance prediction.
- aircraft engine /
- fan speed correction /
- similarity theory /
- support vector regression machine /
- genetic algorithm /
- variable index factor

HTML

参考文献(18)

[1]	郭迎清,李睿,薛薇.航空发动机状态监控系统研究[J].航空发动机,2010,36(5):39-43. GUO Yingqing,LI Rui,XUE Wei.Study on aeroengine condition monitoring system[J].Aeroengine,2010,36(5):39-43.(in Chinese)
[2]	唐庆如,敖良忠,夏存江,等.CFM56-7B发动机航线维护教程[M].成都:四川大学出版社,2003:44-57.
[3]	陕振勇.航空发动机气路参数偏差值模型研究与应用[D].哈尔滨:哈尔滨工业大学,2012. SHAN Zhenyong.Research on aeroengine gas path parameter deviation model and its application[D].Harbin:Harbin Institute of Technology,2012.(in Chinese)
[4]	崔智全.民航发动机气路参数偏差值挖掘方法及其应用研究[D].哈尔滨:哈尔滨工业大学,2013. CUI Zhiquan.Civil aeroengine gas path parameter deviation mining method with application[D].Harbin:Harbin Institute of Technology,2013.(in Chinese)
[5]	林兆福,范作民.发动机基线方程的建立和应用[J].中国民航学院学报,1992,10(4):20-32. LIN Zhaofu,FAN Zuomin.Trend analysis of jet engine gas dynamic and thermodynamic parameters[J].Journal of Civil Aviation Insitute of China,1992,10(4):20-32.(in Chinese)
[6]	钟诗胜,崔智全,付旭云.Rolls-Royce发动机基线挖掘方法[J].计算机集成制造系统,2010,16(10):2265-2270. ZHONG Shisheng,CUI Zhiquan,FU Xuyun.Baseline mining method of RR's engine[J].Computer Integrated Manufacturing Systems,2010,16(10):2265-2270.(in Chinese)
[7]	GE Aviation. Diagnostics trend interpretation training[M]. 5th ed.Shanghai:GE Aviation,2009.
[8]	潘慕绚,黄金泉.基于相似理论的航空发动机转速自适应PID控制[J].推进技术,2003,24(5):429-431. PAN Muxuan,HUANG Jinquan.Adaptive PID control for aeroengine by on similarity theory[J].Journal of Propulsion Technology,2003,24(5):429-431.(in Chinese)
[9]	彭云飞.航空发动机状态参数处理技术及其应用研究[D].哈尔滨:哈尔滨工业大学,2009. PENG Yunfei.Research on processing technique of aeroengine condition parameters and its application[D].Harbin:Harbin Institute of Technology,2009.(in Chinese)
[10]	钟诗胜,崔智全,王体春,等.基于偏差值的航空发动机参数标准化修正模型[J].航空动力学报,2012,27(11):2592-2598. ZHONG Shisheng,CUI Zhiquan,WANG Tichun,et al.Corrected standardization model of aero-engine parameter based on deviation[J].Journal of Aerospace Power,2012,27(11):2592-2598.(in Chinese)
[11]	闫锋,付为刚.航空发动机高压转子转速(N2)基线的建模方法[J].机械设计与制造,2015(1):148-151. YAN Feng,FU Weigang.A modeling method for high compressor rotor speed(N2)baseline of the aero-engine[J].Machinery Design and Manufacture,2015(1):148-151.(in Chinese)
[12]	付金华,闫锋.航空发动机排气温度基线建模方法[J].航空计算技术,2014,44(6):49-54. FU Jinhua,YAN Feng.A method of modeling exhaust gas temperature baseline of aeroengine[J].Aeronautical Computing Technique,2014,44(6):49-54.(in Chinese)
[13]	田英杰.支持向量回归机及其应用研究[D].北京:中国农业大学,2005. TIAN Yingjie.Support vector regression and its application[D].Beijing:China Agricultural Univerisity,2005.(in Chinese)
[14]	丁世飞,齐丙娟,谭红艳.支持向量机理论与算法研究综述[J].电子科技大学学报,2011,40(1):2-10. DING Shifei,QI Bingjuan,TAN Hongyan.An overview on theory and algorithm of support vector machines[J].Journal of University of Electronic Science and Technology of China,2011,40(1):2-10.(in Chinese)
[15]	李海生.支持向量机回归算法与应用研究[D].广州:华南理工大学,2005. LI Haisheng.Algorithm and application research of support vector machine regression[D].Guangzhou:South China University of Technology,2005.(in Chinese)
[16]	林升梁,刘志.基于RBF核函数的支持向量机参数选择[J].浙江工业大学学报,2007,35(2):163-167. LIN Shengliang,LIU Zhi.Parameter selection in SVM with RBF kernel function[J].Journal of Zhejiang University of Technology,2007,35(2):163-167.(in Chinese)
[17]	冯振华,杨洁明.SVM回归的参数选择探讨[J].机械工程与自动化,2007(3):17-18,22. FENG Zhenhua,YANG Jieming.Practical selection of support vector machine parameters for SVM regression[J].Mechanical Engineering and Automation,2007(3):17-18,22.(in Chinese)
[18]	王小川,史峰,郁磊,等.MATLAB神经网络43个案例分析[M].北京:北京航空航天大学出版社,2011:127-136.