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

基于UGF-GO法的EWIS退化系统可靠性分析

曹慧 段富海 江秀红

曹慧, 段富海, 江秀红等 . 基于UGF-GO法的EWIS退化系统可靠性分析[J]. 北京航空航天大学学报, 2019, 45(6): 1153-1161. doi: 10.13700/j.bh.1001-5965.2018.0586
引用本文: 曹慧, 段富海, 江秀红等 . 基于UGF-GO法的EWIS退化系统可靠性分析[J]. 北京航空航天大学学报, 2019, 45(6): 1153-1161. doi: 10.13700/j.bh.1001-5965.2018.0586
CAO Hui, DUAN Fuhai, JIANG Xiuhonget al. Degradation system reliability analysis of EWIS based on UGF-GO methodology[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(6): 1153-1161. doi: 10.13700/j.bh.1001-5965.2018.0586(in Chinese)
Citation: CAO Hui, DUAN Fuhai, JIANG Xiuhonget al. Degradation system reliability analysis of EWIS based on UGF-GO methodology[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(6): 1153-1161. doi: 10.13700/j.bh.1001-5965.2018.0586(in Chinese)

基于UGF-GO法的EWIS退化系统可靠性分析

doi: 10.13700/j.bh.1001-5965.2018.0586
详细信息
    作者简介:

    曹慧 女, 博士研究生。主要研究方向:系统可靠性分析、性能退化研究

    段富海 男, 博士, 教授, 博士生导师。主要研究方向:系统可靠性、测试性研究

    江秀红  女, 博士, 副教授, 硕士生导师。主要研究方向:可靠性分析、预测维修

    通讯作者:

    段富海, E-mail: duanfh@dlut.edu.cn

  • 中图分类号: V242.4+1;TB114.3

Degradation system reliability analysis of EWIS based on UGF-GO methodology

More Information
  • 摘要:

    针对飞机电气线路互联系统(EWIS)差异性大、随时间退化严重、可靠性建模困难等问题,将通用生成函数(UGF)和GO法融合,提出了基于UGF-GO法的EWIS退化可靠性分析方法。首先,考虑EWIS各连接部件使用性能及环境的差异性,利用含随机参数的Wiener退化过程模型建立部件可靠性仿真模型,采用马尔可夫链蒙特卡罗(MCMC)算法对模型中的未知参数进行估计,并与传统二步法参数估计值进行对比,得到较为精确的系统部件退化可靠性曲线。其次,在分析系统退化可靠性时,利用UGF-GO法对某飞机EWIS结构可靠性进行建模及计算。最后,以某飞机电气线路互联系统为例,结合部件退化可靠性计算结果,评估系统在不同给定阈值下可靠性水平。结果表明:UGF-GO法可有效解决系统退化状态的可靠性分析问题。

     

  • 图 1  主设备汇流条性能退化仿真数据

    Figure 1.  Performance degradation simulation data of main equipment busbar

    图 2  电子设备系统GO图

    Figure 2.  GO figure of electronic equipment system

    图 3  某飞机电气线路互联系统设计方案

    Figure 3.  Design scheme of an aircraft's EWIS

    图 4  四种汇流条退化可靠性曲线

    Figure 4.  Degraded reliability curve of four kinds of busbar

    图 5  某飞机电气线路互联系统GO图

    Figure 5.  GO figure of an aircraft's EWIS

    图 6  不同阈值下的系统可靠性曲线

    Figure 6.  System reliability curves under different thresholds

    表  1  主设备汇流条可靠性模型参数估计

    Table  1.   Parameter estimate for reliability model of main equipment busbar

    参数 期望 方差 置信区间(置信水平为0.95)
    μβ 0.447 0 0.017 7 [0.340 0,0.545 6]
    σβ2 0.005 0 0.009 6 [0.000 3,0.007 6]
    σ2 0.222 3 0.371 6 [0.129 0,0.301 0]
    下载: 导出CSV

    表  2  电子设备系统操作符数据

    Table  2.   Operator data of electronic equipment system

    操作符编号 操作符类型 状态概率
    pi, 0 pi, 1
    1 5 0.01 0.99
    2 1 0.05 0.95
    3 1 0.10 0.90
    4 1 0.05 0.95
    5 1 0.10 0.90
    下载: 导出CSV

    表  3  电子设备系统可靠性结果对比

    Table  3.   Reliability result comparison of electronic equipment system

    输出信号 概率公式算法 UGF-GO法
    pi, 0 pi, 1 pi, 0 pi, 1
    Po, 3 0.846 450 0.153 550 0.855 000 0.145 000
    Po, 5 0.846 450 0.153 550 0.855 000 0.145 000
    Po, 6(未修正) 0.976 422 0.023 577 0.978 975 0.021 025
    Po, 6(修正后) 0.969 185 0.030 814 0.969 185 0.030 815
    下载: 导出CSV

    表  4  二步法与MCMC算法参数估计值对比

    Table  4.   Comparison of parameter estimate between two-step algorithm and MCMC algorithm

    汇流条 二步法 MCMC算法
    μβ σβ2 σ2 μβ σβ2 σ2
    主设备 0.441 4 0.011 9 0.278 6 0.447 0 0.005 0 0.222 3
    电子设备 0.431 1 0.014 1 0.319 7 0.421 9 0.005 1 0.221 7
    非必需设备 0.473 9 0.005 5 0.207 0 0.464 1 0.004 5 0.201 0
    蓄电池设备 0.499 8 0.005 1 0.224 8 0.479 3 0.005 0 0.218 9
    下载: 导出CSV

    表  5  某飞机电气线路互联系统操作符数据

    Table  5.   Operator data of an aircraft's EWIS

    编号 类型 名称 状态概率
    pi, 0 pi, 1 pi, 2
    1 5 电源 0.999 984 - 0.000 016
    2~6 1 导通控制 0.999 995 - 0.000 005
    7 1 主设备汇流条 - R1(t) 1-R1(t)
    8, 9 1 电子设备汇流条 - R2(t) 1-R2(t)
    10 2 或门 - - -
    11 1 非必需设备汇流条 - R3(t) 1-R3(t)
    12 1 内部供电开关 0.999 995 - 0.000 005
    13 1 外部供电开关 0.999 989 - 0.000 011
    14 2 或门 - - -
    15 1 蓄电池设备汇流条 - R4(t) 1-R4(t)
    16 10 与门 - - -
    下载: 导出CSV

    表  6  不同阈值系统可靠性结果对比

    Table  6.   Comparison of system reliability results under different thresholds

    时间/
    (103h)
    失效阈值
    5 mΩ 10 mΩ 15 mΩ 20 mΩ
    0.5 0.999 869 23 0.999 869 23 0.999 911 11 0.999 952 99
    1.0 0.983 131 70 0.983 201 29 0.991 532 16 0.999 933 62
    1.5 0.807 300 25 0.814 910 50 0.900 868 99 0.995 894 56
    2.0 0.410 376 10 0.455 760 56 0.650 608 32 0.928 757 82
    2.5 0.111 053 74 0.161 576 30 0.328 864 11 0.669 353 15
    3.0 0.017 385 46 0.037 127 48 0.107 027 91 0.308 530 88
    3.5 0.001 890 51 0.005 873 75 0.022 638 82 0.087 255 26
    下载: 导出CSV
  • [1] WANG W, WANG P.Effect of environments on EWIS failure rate estimate[J].Procedia Engineering, 2011, 17:473-479. doi: 10.1016/j.proeng.2011.10.057
    [2] MEEKER W Q, HAMADA M.Statistical tools for the rapid development and evaluation of high-reliability products[J].IEEE Transactions on Reliability, 1995, 44(2):187-198. doi: 10.1109/24.387370
    [3] LEVITEN G.The universal generating function in reliability analysis and optimization[M].Berlin:Springer, 2005.
    [4] LI W J, PHAM H.Reliability modeling of multi-state degraded systems with multi-competing failures and random shocks[J].IEEE Transactions on Reliability, 2005, 54(2):297-303. doi: 10.1109/TR.2005.847278
    [5] WANG G, DUAN F, ZHOU Y.Reliability evaluation of multi-state series systems with performance sharing[J].Reliability Engineering & System Safety, 2018, 173:58-63. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=20b2ec486f5b90cb70fe3076273c25fb
    [6] LI J, COIT D W, ELSAYED E A.Reliability modeling of a series system with correlated or dependent component degradation processes[C]//International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering.Piscataway, NJ: IEEE Press, 2011: 388-393.
    [7] FAGHIH-ROOHI S F, MIN X, KIEN M G, et al.Dynamic availability assessment and optimal component design of multi-state weighted k-out-of-n systems[J].Reliability Engineering & System Safety, 2014, 123:57-62. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=ed283337f3132a4d3e3111a11b202def
    [8] LI X, JIANG T M, MA J, et al.State tree analysis of FOG based on drift brownian motion[C]//International Conference on Reliability, Maintainability and Safety.Piscataway, NJ: IEEE Press, 2009: 1322-1326.
    [9] 彭宝华, 周经伦, 刘学敏.元器件性能退化信息的系统性能可靠性评估[J].火力与指挥控制, 2011, 36(10):148-151. doi: 10.3969/j.issn.1002-0640.2011.10.039

    PENG B H, ZHOU J L, LIU X M.System performance reliability assessment based on degradation data from components[J].Fire Control & Command Control, 2011, 36(10):148-151(in Chinese). doi: 10.3969/j.issn.1002-0640.2011.10.039
    [10] NIKULIN M S, LIMNIOS N, BALARISHNAN N, et al.Advances in degradation modeling[M].Boston:Birkhäuser Boston, 2010.
    [11] 沈祖培, 黄祥瑞.GO法原理及应用:一种系统可靠性分析方法[M].北京:清华大学出版社, 2004.

    SHEN Z P, HUANG X R.Principle and application of GO methodology:A system reliability analysis methodology[M].Beijing:Tsinghua University Press, 2004(in Chinese).
    [12] YE Z S, XIE M.Stochastic modelling and analysis of degradation for highly reliable products[J].Applied Stochastic Models in Business & Industry, 2015, 31(1):16-32. http://cn.bing.com/academic/profile?id=ff6ebbbce0b6178e638094be85f50493&encoded=0&v=paper_preview&mkt=zh-cn
    [13] SHERIF Y.S, SMITH M L.First-passage time distribution of brownian motion as a reliability model[J].IEEE Transactions on Reliability, 2009, R-29(5):425-426.
    [14] HAO H B, LI C P.Reliability assessment and residual life prediction method based on Wiener process and current degradation quantity[J].Engineering Letters, 2016, 24(2):172-177.
    [15] LI C P, HAO H B.Degradation data analysis using Wiener process and MCMC approach[J].Engineering Letters, 2017, 25(3):234-238.
    [16] FAN T H, CHEN C H.A Bayesian predictive analysis of step-stress accelerated tests in gamma degradation-based processes[J].Quality & Reliability Engineering International, 2017, 33(7):1417-1424. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=e081a80c593456c1a0d910ff83a23d96
    [17] JAIN V.Computational statistics handbook with MATLAB[J].Journal of the Royal Statistial Society:Series A(Statistics in Society), 2009, 172(4):942-943.
    [18] 沈祖培, 高佳.GO法原理和改进的定量分析方法[J].清华大学学报, 1999, 39(6):15-19. doi: 10.3321/j.issn:1000-0054.1999.06.005

    SHEN Z P, GAO J.GO methodology and improved quantification of system reliability[J].Journal of Tsinghua University, 1999, 39(6):15-19(in Chinese). doi: 10.3321/j.issn:1000-0054.1999.06.005
    [19] REN Y, FAN D, WANG Z, et al.System dynamic behavior modelling based on extended GO methodology[J].IEEE Access, 2018, 6:22513-22523. doi: 10.1109/ACCESS.2018.2816165
    [20] LENVITIN G.A universal generating function approach for the analysis of multi-state systems with dependent elements[J].Reliability Engineering & System Safety, 2004, 84(3):285-292.
    [21] JOSEPHLU C J, MEEKER W Q.Using degradation measures to estimate a time-to-failure distribution[J].Technometrics, 1993, 35(2):161-174. doi: 10.1080/00401706.1993.10485038
    [22] 朱新宇, 王有隆, 胡焱.民航飞机电气仪表及通信系统[M].成都:西南交通大学出版社, 2006.

    ZHU X Y, WANG Y L, HU Y.Electrical instrument and communications systems in civil aircraft[M].Chengdu:Southwest Jiaotong University Press, 2006(in Chinese).
  • 加载中
图(6) / 表(6)
计量
  • 文章访问数:  578
  • HTML全文浏览量:  41
  • PDF下载量:  336
  • 被引次数: 0
出版历程
  • 收稿日期:  2018-10-13
  • 录用日期:  2019-01-04
  • 网络出版日期:  2019-06-20

目录

    /

    返回文章
    返回
    常见问答