留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

考虑使用因素的涡扇发动机排气温度换算方法

张红涛 骆广琦 杨武奎 陈礼顺

张红涛, 骆广琦, 杨武奎, 陈礼顺. 考虑使用因素的涡扇发动机排气温度换算方法[J]. 航空动力学报, 2018, 33(6): 1492-1499. doi: 10.13224/j.cnki.jasp.2018.06.023
引用本文: 张红涛, 骆广琦, 杨武奎, 陈礼顺. 考虑使用因素的涡扇发动机排气温度换算方法[J]. 航空动力学报, 2018, 33(6): 1492-1499. doi: 10.13224/j.cnki.jasp.2018.06.023
Conversion methods of turbofan-engine exhaust gas temperaturewith consideration of use factors[J]. Journal of Aerospace Power, 2018, 33(6): 1492-1499. doi: 10.13224/j.cnki.jasp.2018.06.023
Citation: Conversion methods of turbofan-engine exhaust gas temperaturewith consideration of use factors[J]. Journal of Aerospace Power, 2018, 33(6): 1492-1499. doi: 10.13224/j.cnki.jasp.2018.06.023

考虑使用因素的涡扇发动机排气温度换算方法

doi: 10.13224/j.cnki.jasp.2018.06.023
基金项目: APTD-1402-05

Conversion methods of turbofan-engine exhaust gas temperaturewith consideration of use factors

  • 摘要: 针对某型涡扇发动机厂内排气温度换算值验收合格而外场地面检查实测值偶有不合格的问题,分析了只考虑大气温度单一因素的排气温度换算方法的缺陷。提出了一种综合考虑非标准大气和调节规律使用因素的换算方法,建立了数学模型,计算得到了非标准大气的修正系数和调节规律的修正系数,并经试车试验验证。结果表明:提出的考虑使用因素的换算方法符合发动机的实际使用条件,所获得的修正系数与试车试验数据的相对误差小于1.3%,有效解决了排气温度厂内验收合格而外场地面开车不合格的问题。

     

  • [1] 陈果.用结构自适应神经网络预测航空发动机性能趋势[J].航空学报,2007,28(3):535-539.CHEN Guo.Forecasting engine perfromance trend by using structure self-adaptive neural network[J].Acta Aeronautica et Astronauica Sinica,2007,28(3):535-539.(in Chinese)
    [2] 钟诗胜,李洋.基于小波过程神经网络的飞机民用航空发动机状态监视[J].航空学报,2007,28(1):68-71.ZHONG Shisheng,LI Yang.Condition monitoring of aero-engine based on wavelet process neural networks[J].Acta Aeronautica et Astronauica Sinica,2007,28(1):68-71.(in Chinese)
    [3] 史永胜,彭朋,宋云雪.基于边界值的多元混沌发动机性能预测算法[J].航空动力学报,2012,27(1):211-216.SHI Yongsheng,PENG Peng,SONG Yunxue.Multivariable chaotic arithmetic for aero-engine performance forecasting based on boundary values[J].Journal of Aerospace Power,2012,27(1):211-216.(in Chinese)
    [4] BANKS J,REICHARD K,CROW E,et al.How engineers can conduct cost-benefit analysis for PHM systems[J].IEEE Aerospace and Electronic Systems Magazine,2009,24(3):176-180.
    [5] 毛华军.燃气轮机排气温度监视和保护功能分析[J].华电技术,2009,31(8):11-15.MAO Huajun.Analysis of exhaust temperature monitor and protection function for gas turbine[J].Huadian Technology,2009,31(8):11-15.(in Chinese)
    [6] 于文武,许春生.提高民航发动机起飞EGT裕度的措施[J].航空维修与工程,2007(3):33-35.YU Wenwu,XU Chunsheng.Measures to increase civil aeroengines take off EGT margin[J].Aviation Maintenance and Engineering,2007(3):33-35.(in Chinese)
    [7] 郝英.发动机起飞EGT裕度的估算[J].航空维修与工程,2004(2):39-40.HAO Ying.Estimation of aero-engine takeoff EGT margin[J].Aviation Maintenance and Engineering,2004(2):39-40.(in Chinese)
    [8] 何立明.飞机推进系统原理[M].北京:国防工业出版社,2006.
    [9] LEE Y K,MAVRIS D N,VOLOVOI V V,et al.A fault diagnosis method for industrial gas turbines using Bayesian data analysis[J].Journal of Engineering for Gas Turbines and Power,2010,132(4):041602.1-041602.6.
    [10] LI Y G.Performance analysis based gas turbine diagnostics:a review[J].Journal of Power and Energy,2002,216(5):363-377.
    [11] HE H X,LI N,ZHENG G F,et al.Anomaly detection based on multi-detector fusion used in turbine[J].Journal of Harbin Institute of Technology,2013,20(1):113-117.
    [12] PATRICK H P E,HA D.Exhaust gas temperature capabilities now in system 1(R) software[J].Product Update,2005,25(1):88-89.
    [13] LIU X,JEFFRIES J B,HANSON R K,et al.Development of a tunable diode laser sensor for measurements of gas turbine exhaust temperature[J].Applied Physics:B,2006,82(3):469-478.
    [14] 钟诗胜,雷达,丁钢.卷积和离散过程神经网络及其在航空发动机排气温度预测中的应用[J].航空学报,2012,33(3):438-444.ZHONG Shisheng,LEI Da,DING Gang.Convolution sum discrete process neural network and its application in aero-engine exhaust gas temperature prediction[J].Acta Aeronautica et Astronautica Sinica,2012,33(3):438-444.(in Chinese)
    [15] 《航空发动机设计手册》总编委会.航空发动机设计手册:第5册 涡喷及涡扇发动机总体[M].北京:航空工业出版社,2001.
    [16] 付为刚,李梦,尚永锋,等.基于支持向量机的涡扇发动机EGT回归分析[J].机械设计与制造,2015(10):129-131.FU Weigang,LI Meng,SHANG Yongfeng,et al.Regression analysis based on support vector machine for turbofan engines exhaust gas temperature[J].Machinery Design and Manufacture,2015(10):129-131.(in Chinese)
    [17] 王伟影,赵宁波,唐瑞,等.燃气轮机排气温度异常检测及诊断[J].哈尔滨工程大学学报,2015,36(3):337-342.WANG Weiying,ZHAO Ningbo,TANG Rui,et al.Anomaly detection and diagnosis of gas turbine exhaust gas temperature[J].Journal of Harbin Engineering University,2015,36(3):337-342.(in Chinese)
    [18] 陈娇,王永泓,翁史烈.广义回归神经网络在燃气轮机排气温度传感器故障检测中的应用[J].中国电机工程学报,2009,29(32):92-97.CHEN Jiao,WANG Yonghong,WENG Shilie.Application of general regression neural network in fault detection of exhaust temperature sensors on gas turbines[J].Proceedings of the CSEE,2009,29(32):92-97.(in Chinese)
  • 加载中
计量
  • 文章访问数:  879
  • HTML浏览量:  155
  • PDF量:  487
  • 被引次数: 0
出版历程
  • 收稿日期:  2017-06-22
  • 刊出日期:  2018-06-28

目录

    /

    返回文章
    返回