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

竞争风险模型下变环境的发动机叶片可靠性分析

蔡景 李鑫 肖罗椿 陈康 苏艳

蔡景, 李鑫, 肖罗椿, 陈康, 苏艳. 竞争风险模型下变环境的发动机叶片可靠性分析[J]. 航空动力学报, 2017, 32(2): 398-404. doi: 10.13224/j.cnki.jasp.2017.02.018
引用本文: 蔡景, 李鑫, 肖罗椿, 陈康, 苏艳. 竞争风险模型下变环境的发动机叶片可靠性分析[J]. 航空动力学报, 2017, 32(2): 398-404. doi: 10.13224/j.cnki.jasp.2017.02.018
Reliability analysis of engine blade under varied environment with competing risk model[J]. Journal of Aerospace Power, 2017, 32(2): 398-404. doi: 10.13224/j.cnki.jasp.2017.02.018
Citation: Reliability analysis of engine blade under varied environment with competing risk model[J]. Journal of Aerospace Power, 2017, 32(2): 398-404. doi: 10.13224/j.cnki.jasp.2017.02.018

竞争风险模型下变环境的发动机叶片可靠性分析

doi: 10.13224/j.cnki.jasp.2017.02.018
基金项目: 国家自然科学基金(61079013,U1233114); 江苏省自然科学基金(BK2011737)

Reliability analysis of engine blade under varied environment with competing risk model

  • 摘要: 针对航空发动机转子叶片的恶劣工况导致其存在多种故障模式,各种故障的失效与使用环境紧密关联,给航空发动机转子叶片的可靠性分析或风险控制带来了难度这一问题,从转子叶片的磨损和裂纹两种主要故障模式特点出发,研究了变环境下的转子叶片磨损故障模型和疲劳裂纹故障模型,提出了一种基于竞争风险模型的转子叶片可靠性分析方法,并给出了求解算法;以某高压涡轮转子叶片为例进行了分析研究.结果表明:在可靠性分析中采用单个故障模型比竞争风险模型风险更大;且在竞争风险模型下,如果不考虑推力环境的影响,以不可靠度要求0.1为例,相应风险增加了33%,验证了所提方法的实用性.

     

  • [1] Zaretsky E V,Litt J S,Hendricks R C.Determination of turbine blade life from engine field data structures,structural dynamics,and materials conference[J].Journal of Propulsion and Power,2012,28(6):1156-1167.
    [2] 周胜田.航空发动机叶片疲劳的损伤力学研究及外物损伤影响[D].沈阳:东北大学,2008. ZHOU Shengtian.Study onfatigue of airengine blades by damage mechanics and influence of foreign object damage[D].Shenyang:Northeastern University,2008.(in Chinese)
    [3] Hou J,Wicks B J,Antoniou R A.An investigation of fatigue failures of turbine blades in a gas turbine engine by mechanical analysis[J].Engineering Failure Analysis,2002,9(2):201-211.
    [4] Vittal S,Hajela P,Joshi A.Review of approaches to gas turbine life management[R].Taizhou:10th AIAA/ISSMO Multidisciplinary Analysis and Optimization,2004.
    [5] Giantomassi A,Ferracuti F,Benini A,et al.Hidden Markov model for health estimation and prognosis of turbofan engines[R].ASME Paper GT2011-48174,2011.
    [6] Ray A K,Das G,Ranganath V R,et al.Failure of connecting pins of a compressor disc in an aero engine[J].Engineering Failure Analysis,2004,11(4):613-617.
    [7] Orsagh R,Roemer M,Sheldon J,et al.A comprehensive prognostics approach for predicting gas turbine engine bearing life[R].ASME Paper GT2004-53965,2004.
    [8] 公杰.某航空发动机使用载荷对其整机寿命和可靠性的影响研究[D].成都:电子科技大学,2012. GONG Jie.The study on theimpact of engines load on engines life and reliability[D].Chengdu:University of Electronic Science and Technology of China,2012.(in Chinese)
    [9] Biallas G,Essert M,Maier H J.Influence of environment on fatigue mechanisms in hightemperature titanium alloy IMI834[J].International Journal of Fatigue,2005,27(10):1485-1493.
    [10] Gagg C R,Lewis P R.Wear as a product failure mechanismoverview and case studies[J].Engineering Failure Analysis,2007,14(8):1618-1640.
    [11] Vardar N,Ekerim A.Failure analysis of gas turbine blades in a thermal power plant[J].Engineering Failure Analysis,2007,14(4):743-749.
    [12] Gebraeel N Z,Lawley M A,Li R,et al.Residuallife distributions from component degradation signals:a bayesian approach[J].IIE Transactions,2005,37(6):543-557.
    [13] Gao X,Dodds R H,Tregoning R L,et al.A Weibull stress model to predict cleavage fracture in plates containing surface cracks[J].Fatigue and Fracture of Engineering Materials and Structures,1999,22(6):481-493.
    [14] Weibull W.Analysis of fatigue test results[M].Oxford,London,New York,Paris:Pergamon Press,1961.
    [15] 林静,韩玉启,朱慧明.一种多重Weibull回归模型在竞争失效分析中的应用[J].系统仿真学报,2006,8(2):199-202. LIN Jing,HAN Yuqi,ZHU Huiming.Application of polyweibull regression model in analysis with competing causes of failure[J].Journal of System Simulation,2006,8(2):199-202.(in Chinese)
    [16] 赵慧江.威布尔回归模型的统计诊断[D].贵阳:贵州财经学院,2009. ZHAO Huijiang.Thediagnostics and influence of Weibull regression model[D].Guiyang:Guizhou College Finance and Economics,2009.(in Chinese)
    [17] David H A,Moeschberger M L.The theory of competing risks[M].London:Griffin,1978.
    [18] Smith R L.Weibull regression models for reliability data[J].Reliability Engineering and System Safety,1991,34(1):55-76.
    [19] 袁锴.民用飞机部件可靠性分析与维修决策优化方法研究[D].南京:南京航空航天大学,2013. YUAN Kai.Research onmethods of reliability analysis and maintenance decisionmaking optimization for civil aircraft component[D].Nanjing:Nanjing University of Aeronautics and Astronautics,2013.(in Chinese)
    [20] Nelson W B.Applied life data analysis[M].New York:John Wiley and Sons,2005.
    [21] Ramíreza P,Carta J A.Influence of the data sampling interval in the estimation of the parameters of the Weibull wind speed probability density distribution:a case study[J].Energy Conversion and Management,2005,45(15):2419-2438.
  • 加载中
计量
  • 文章访问数:  817
  • HTML浏览量:  0
  • PDF量:  415
  • 被引次数: 0
出版历程
  • 收稿日期:  2015-06-04
  • 刊出日期:  2017-02-28

目录

    /

    返回文章
    返回