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

非完美维修下民航发动机剩余寿命预测

曹惠玲 崔科璐 郭静

曹惠玲,崔科璐,郭静. 非完美维修下民航发动机剩余寿命预测[J]. 机械科学与技术,2020,39(12):1969-1974 doi: 10.13433/j.cnki.1003-8728.20200001
引用本文: 曹惠玲,崔科璐,郭静. 非完美维修下民航发动机剩余寿命预测[J]. 机械科学与技术,2020,39(12):1969-1974 doi: 10.13433/j.cnki.1003-8728.20200001
Cao Huiling, Cui Kelu, Guo Jing. Prediction on Residual Life of Civil Aviation Engine under Imperfect Maintenance[J]. Mechanical Science and Technology for Aerospace Engineering, 2020, 39(12): 1969-1974. doi: 10.13433/j.cnki.1003-8728.20200001
Citation: Cao Huiling, Cui Kelu, Guo Jing. Prediction on Residual Life of Civil Aviation Engine under Imperfect Maintenance[J]. Mechanical Science and Technology for Aerospace Engineering, 2020, 39(12): 1969-1974. doi: 10.13433/j.cnki.1003-8728.20200001

非完美维修下民航发动机剩余寿命预测

doi: 10.13433/j.cnki.1003-8728.20200001
基金项目: PHM机载系统预诊断与告警模型研究(20190102010200)与民航大学博士启动基金项目(QD02s04)资助
详细信息
    作者简介:

    曹惠玲(1962−),教授,博士,研究方向为航空发动机状态监控、寿命预测与性能分析;hlcao05@163.com

  • 中图分类号: V19

Prediction on Residual Life of Civil Aviation Engine under Imperfect Maintenance

  • 摘要: 针对现阶段剩余寿命(RUL)预测方法没有考虑在发动机性能衰退阶段维修因素影响的问题,提出了以考虑非完美维修下的性能衰退模型预测民航发动机RUL的方法。采用带漂移点的Wiener过程对民航发动机的性能退化进行建模。根据历史性能退化数据以及历史维修记录数据,通过极大似然估计算法对模型参数进行估计,实现对航空发动机的RUL预测。通过航空公司实际发动机机载快速存取记录器(QAR)数据进行模型验证,结果表明:该方法能够更好地跟踪发动机实际性能退化过程,预测精度较高,能为民航发动机维修计划的制定提供依据。
  • 图  1  经历单次维修发动机EGTM退化轨迹

    图  2  发动机的EGTM衰退轨迹

    图  3  发3的退化轨迹与两种模型预测轨迹

    图  4  预测结果对比图

    表  1  维修后发动机EGTM变化表

    NUMESNEGTM_B/℃EGTM_A/℃△EGTM/℃
    1 4***1 25.76 33.22 7.46
    2 4***1 15.86 30.58 14.72
    3 4***2 37.10 42.27 5.17
    4 4***2 34.47 39.54 5.07
    $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $
    56 4**29 16.63 22.25 5.62
    57 4**30 26.49 34.02 4.53
    下载: 导出CSV

    表  2  基准模型与改进模型参数估计值

    ESN${\hat \mu _{\theta st}}$${\hat \sigma _{\theta st}}$${\sigma _{{{st}}}}$${\hat \mu _\theta }$${\hat \sigma _\theta }$$\hat \sigma $
    4***1 0.182 0.029 0.024 0.324 0.028 0.022
    4***2 0.177 0.034 0.032 0.341 0.026 0.028
    $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $
    4***9 0.201 0.042 0.022 0.285 0.027 0.023
    4**10 0.199 0.030 0.024 0.318 0.021 0.024
    下载: 导出CSV
  • [1] Pecht M. Prognostics and health management of electronics[M]. Hoboken: John Wiley, 2008.
    [2] Sun B, Zeng S K, Kang R, et al. Benefits and challenges of system prognostics[J]. IEEE Transactions on Reliability, 2012, 61(2): 323-335
    [3] Si X S, Wang W B, Hu C H, et al. A Wiener-process-based degradation model with a recursive filter algorithm for remaining useful life estimation[J]. Mechanical Systems and Signal Processing, 2013, 35(1-2): 219-237
    [4] Wang Z Q, Hu C H, Wang W B, et al. A simulation-based remaining useful life prediction method considering the influence of maintenance activities[C]//Proceedings of 2014 Prognostics and System Health Management Conference. Zhangjiajie: IEEE, 2014: 284-289.
    [5] Whitmore G A, Schenkelberg F. Modelling accelerated degradation data using Wiener diffusion with a time scale transformation[J]. Lifetime Data Analysis, 1997, 3(1): 27-45
    [6] Tseng S T, Tang J, Ku I H. Determination of burn-in parameters and residual life for highly reliable products[J]. Naval Research Logistics, 2003, 50(1): 1-14
    [7] 朱磊, 左洪福, 蔡景. 基于Wiener过程的民用航空发动机性能可靠性预测[J]. 航空动力学报, 2013, 28(5): 1006-1012

    Zhu L, Zuo H F, Cai J. Performance reliability prediction for civil aviation aircraft engine based on Wiener process[J]. Journal of Aerospace Power, 2013, 28(5): 1006-1012 (in Chinese)
    [8] 刘君强, 谢吉伟, 左洪福, 等. 基于随机Wiener过程的航空发动机剩余寿命预测[J]. 航空学报, 2014, 36(2): 564-574

    Liu J Q, Xie J W, Zuo H F, et al. Residual lifetime prediction for aeroengines based on Wiener process with random effects[J]. Acta Aeronautica et Astronautica Sinica, 2014, 36(2): 564-574 (in Chinese)
    [9] 黄亮, 刘君强, 贡英杰. 基于Wiener过程的发动机多阶段剩余寿命预测[J]. 北京航空航天大学学报, 2018, 44(5): 1081-1087

    Huang L, Liu J Q, Gong Y J. Multi-phase residual life prediction of engines based on Wiener process[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(5): 1081-1087 (in Chinese)
    [10] 付旭云, 钟诗胜, 张慕楠. 一种改进的航空发动机剩余寿命预测方法[J]. 哈尔滨工业大学学报, 2013, 45(5): 51-55 doi: 10.11918/j.issn.0367-6234.2013.05.010

    Fu X Y, Zhong S S, Zhang M N. An improved method for aeroengine residual life prediction[J]. Journal of Harbin Institute of Technology, 2013, 45(5): 51-55 (in Chinese) doi: 10.11918/j.issn.0367-6234.2013.05.010
    [11] 石慧, 曾建潮. 考虑非完美维修的实时剩余寿命预测及维修决策模型[J]. 计算机集成制造系统, 2014, 20(9): 2259-2266

    Shi H, Zeng J C. Prediction of real-time remaining useful life and maintenance decision model considering imperfect preventive maintenance[J]. Computer Integrated Manufacturing Systems, 2014, 20(9): 2259-2266 (in Chinese)
    [12] Gebraeel N, Pan J. Prognostic degradation models for computing and updating residual life distributions in a time-varying environment[J]. IEEE Transactions on Reliability, 2008, 57(4): 539-550
    [13] You M Y, Meng G. A predictive maintenance scheduling framework utilizing residual life prediction information[J]. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 2013, 227(3): 185-197
    [14] You M Y, Liu F, Wang W, et al. Statistically planned and individually improved predictive maintenance management for continuously monitored degrading systems[J]. IEEE Transactions on Reliability, 2010, 59(4): 744-753
    [15] 王兆强, 胡昌华, 王文彬, 等. 基于Wiener过程的钢厂风机剩余使用寿命实时预测[J]. 北京科技大学学报, 2014, 36(10): 1361-1368

    Wang Z Q, Hu C H, Wang W B, et al. Wiener process-based online prediction method of remaining useful life for draught fans in steel mills[J]. Journal of University of Science and Technology Beijing, 2014, 36(10): 1361-1368 (in Chinese)
  • 加载中
图(4) / 表(2)
计量
  • 文章访问数:  206
  • HTML全文浏览量:  47
  • PDF下载量:  26
  • 被引次数: 0
出版历程
  • 收稿日期:  2019-06-06
  • 网络出版日期:  2020-12-08
  • 刊出日期:  2020-12-05

目录

    /

    返回文章
    返回