基于狄氏先验分布的机电产品主要失效模式贝叶斯分析

doi:10.3969/j.issn.1000-1093.2012.02.013

兵工学报 ›› 2012, Vol. 33 ›› Issue (2): 209-213.doi: 10.3969/j.issn.1000-1093.2012.02.013

基于狄氏先验分布的机电产品主要失效模式贝叶斯分析

谭源源，张春华，陈循

(国防科学技术大学机电工程与自动化学院, 湖南长沙 410073)

收稿日期:2010-07-23 修回日期:2010-07-23 上线日期:2014-03-04
作者简介:谭源源(1982—)，男，讲师
基金资助:
国家部委资助项目(203020102)

Bayesian Analysis Based on Dirichlet Prior Distribution of Dominant Failure Modes for Electromechanical Products

TAN Yuan-yuan， ZHANG Chun-hua， CHEN Xun

(College of Mechanical Engineering and Automation, National University of Defense Technology, Changsha 410073, Hunan, China)

Received:2010-07-23 Revised:2010-07-23 Online:2014-03-04

摘要/Abstract

摘要： 对于具有多种失效模式的复杂机电产品，主要失效模式分析是产品可靠性设计和试验中非常重要的环节。但目前常用的基于频率分析的定量分析方法，在小样本量场合并不是最优方法。针对这一问题，提出了基于Dirichlet先验分布的Bayes分析方法，实现了小样本量场合的主要失效模式定量分析。在此基础上采用Monte Carlo仿真分析方法的性质，并通过应用算例验证方法的有效性。结果表明，在小样本量场合Bayes方法比频率分析方法的精度更高，能更有效地找出产品的主要失效模式。

关键词: 数理统计学, 主要失效模式, 频率分析, Bayes方法, Dirichlet分布, Monte Carlo仿真

Abstract: For complex electromechanical products with several failure modes, the analysis of dominant failure modes is a key process during reliability design and test. But the frequency analysis, which is commonly used for quantitative analysis at present, is not the best method when data is not plenty. For this problem, Bayesian method based on Dirichlet prior distribution is proposed for quantitative analysis of dominant failure modes in the case of small sample size. Monte Carlo simulation is performed to check the proposed methods and an example is provided. The results show that, Bayesian method is more suitable than the frequency analysis method, and is more effective to find out the dominant failure modes when sample size is small.

Key words: mathematical statistics, dominant failure mode, frequency analysis, Bayesian method, Dirichlet distribution, Monte Carlo simulation

中图分类号:

TB114.3

谭源源，张春华，陈循. 基于狄氏先验分布的机电产品主要失效模式贝叶斯分析[J]. 兵工学报, 2012, 33(2): 209-213.

TAN Yuan-yuan， ZHANG Chun-hua， CHEN Xun. Bayesian Analysis Based on Dirichlet Prior Distribution of Dominant Failure Modes for Electromechanical Products[J]. Acta Armamentarii, 2012, 33(2): 209-213.

参考文献

［1］ Peter L, Kosuke I. Global failure modes and effects analysis: a planning tool for global product development[C]∥Proceedings of International Design Engineering Technical Conference. California: FMEA, 2005: 1-10.
［2］李久祥. 整机加速贮存寿命试验研究[J]. 质量与可靠性, 2004,(4): 14-17.
LI Jiu-xiang. Research on accelerated storage life testing of the whole assembly[J]. Quantity and Reliability, 2004,(4): 14-17. (in Chinese)
［3］贺国芳. 可靠性数据的收集与分析[M]. 北京：国防工业出版社, 1995.
HE Guo-fang. Collection and analysis of reliability data[M]. Beijing: National Defense Industry Press, 1995. (in Chinese)
［4］于捷, 贾亚洲. 数控车床故障模式影响与致命性分析[J]. 哈尔滨工业大学学报, 2005, 37(12): 1725-1727.
YU Jie, JIA Ya-zhou. Failure mode effect and criticality analysis on certain serial CNC lathes[J]. Journal of Harbin Institute of Technology, 2005, 37(12): 1725-1727. (in Chinese)
［5］林震, 李宪珊, 姜同敏, 等. 整机产品加速贮存寿命试验研究思路探讨[J]. 环境与可靠性, 2006,(4): 38-41.
LIN Zhen, LI Xian-shan, JIANG Tong-min, et al. Discussion on accelerated storage life testing of assembly-level products[J]. Environment and Reliability, 2006,(4): 38-41. (in Chinese)
［6］ Mazzuchi T A, Soyer R. A bayes attribute reliability growth model[C]∥Proceedings of Annual Reliability and Maintainability Symposium. Orlando: 1991: 322-325.
［7］茆诗松, 王静龙, 濮晓龙. 高等数理统计（第二版）[M]. 北京：高等教育出版社, 2006.
MAO Shi-song, WANG Jing-long, PU Xiao-long. Advanced mathematical statistics (2nd edition)[M]. Beijing: High Education Press, 2006. (in Chinese)
［8］ Smith A F, Gelfand A E. Bayesian statistics without tears: a sampling-resampling perspective[J]. The American Statistician, 1992,(46): 84-88.

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基于狄氏先验分布的机电产品主要失效模式贝叶斯分析

Bayesian Analysis Based on Dirichlet Prior Distribution of Dominant Failure Modes for Electromechanical Products

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