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

故障预测算法稳定性实时评估方法

于劲松 刘浩 张平 万九卿

于劲松, 刘浩, 张平, 等 . 故障预测算法稳定性实时评估方法[J]. 北京航空航天大学学报, 2014, 40(9): 1208-1212. doi: 10.13700/j.bh.1001-5965.2013.0532
引用本文: 于劲松, 刘浩, 张平, 等 . 故障预测算法稳定性实时评估方法[J]. 北京航空航天大学学报, 2014, 40(9): 1208-1212. doi: 10.13700/j.bh.1001-5965.2013.0532
Yu Jinsong, Liu Hao, Zhang Ping, et al. Real-time evaluation method for stability of fault prognostic algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(9): 1208-1212. doi: 10.13700/j.bh.1001-5965.2013.0532(in Chinese)
Citation: Yu Jinsong, Liu Hao, Zhang Ping, et al. Real-time evaluation method for stability of fault prognostic algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(9): 1208-1212. doi: 10.13700/j.bh.1001-5965.2013.0532(in Chinese)

故障预测算法稳定性实时评估方法

doi: 10.13700/j.bh.1001-5965.2013.0532
基金项目: 国家自然科学基金资助项目(61174020)
详细信息
    作者简介:

    于劲松(1968-),男,江苏滨海人,副教授,jinsong_yu@126.com.

  • 中图分类号: TP202+.1

Real-time evaluation method for stability of fault prognostic algorithm

  • 摘要: 针对现有故障预测算法性能评估指标受实际剩余使用寿命约束的问题,从稳定性角度提出一种评估算法性能的方法。通过研究对象系统健康退化过程,在对象系统实际剩余使用寿命未知情况下,利用可以实时获得的剩余使用寿命预测值和已消耗寿命值,通过计算虚构寿命值的变异系数指标来客观评估故障预测算法的性能。为了验证所提方法的有效性,结合机电作动器故障演化模型仿真生成数据对递归最小二乘和粒子滤波两种故障预测算法的稳定性进行了实时评价。仿真结果表明,所提方法与运用已有指标、在获知剩余使用寿命理想值前提下得出的评估结果保持一致。

     

  • [1] 王志鹏,吕琛,王自力,等.飞机PHM演示验证平台设计技术研究[J].南京理工大学学报,2011,35(增刊):250-255 Wang Zhipeng,Lü Chen,Wang Zili,et al.Design of PHM demonstration and verification platform[J].Journal of Nanjing University of Science and Technology,2011,35(Supplement):250-255(in Chinese)
    [2] Abhinav S,Jose C,Bhaskar S.Evaluating algorithm performance metrics tailored for prognostics[C]//Aerospace Conference.Piscataway,NJ:IEEE,2008:1-13
    [3] Abhinav S,Jose C,Bhaskar S,et al.On applying the prognostic performance metrics[C]//Prognostics and Health Management.New York:IEEE,2009:478-485
    [4] Abhinav S,Jose C,Bhaskar S,et al.Metrics for offline evaluation of prognostic performance[J].International Journal of Prognostic and Health Management,2010,1(1):1-20
    [5] Tang L,Kacprzynski G J,Goebel K,et al.Methodologies for uncertainty management in prognostics[C]//Aerospace conference,2009 IEEE.[S.l.]:IEEE,2009:1-12
    [6] Gu J,Barker D,Pecht M.Uncertainty assessment of prognostics implementation of electronics under vibration loadings[J].Microelectronics Reliability,2007,47(12):1849-1856
    [7] Roemer M J,Dzakowic J,Orsagh R F,et al.Validation and verification of prognostic and health management technologies[C]//Aerospace Conference,2005 IEEE.Atlanta:IEEE,2005:3941-3947
    [8] 梁旭,李行善,张磊,等.支持视情维修的故障预测技术研究[J].测控技术,2007,26(6):5-8 Liang Xu,Li Xingshan,Zhang Lei,et al.Survey of fault prognostics supporting condition based maintenance[J].Measurement and Control Technology,2007,26(6):5-8(in Chinese)
    [9] Shi J Y,Shi M,Wang L,et al.Performance evaluation method of remaining useful life prediction based on pseudo life[C]//Industrial Engineering and Engineering Management.Piscataway,NJ:IEEE,2011:1118-1122
    [10] 吴豪.机电作动器故障预测与健康管理关键技术研究[D].北京:北京航空航天大学,2012 Wu Hao.Key technologies of fault prognosis and health management for electro-mechanical actuator[D].Beijing:Beijing University of Aeronautics and Astronautics,2012(in Chinese)
    [11] Arulampalam M S,Maskell S,Gordon N,et al.A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking[J].IEEE Transactions on Signal Processing,2002,50(2):174-188
    [12] Simon D.Optimal state estimations[M].Hoboken,New Jersey:John Wiley and Sons,2006

  • 加载中
计量
  • 文章访问数:  1212
  • HTML全文浏览量:  14
  • PDF下载量:  578
  • 被引次数: 0
出版历程
  • 收稿日期:  2013-09-23
  • 网络出版日期:  2014-09-20

目录

    /

    返回文章
    返回
    常见问答