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产品性能可靠性评估的时序分析方法

尤 琦 赵 宇 马小兵

尤 琦, 赵 宇, 马小兵等 . 产品性能可靠性评估的时序分析方法[J]. 北京航空航天大学学报, 2009, 35(5): 644-648.
引用本文: 尤 琦, 赵 宇, 马小兵等 . 产品性能可靠性评估的时序分析方法[J]. 北京航空航天大学学报, 2009, 35(5): 644-648.
You Qi, Zhao Yu, Ma Xiaobinget al. Performance reliability assessment for products based on time series analysis[J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(5): 644-648. (in Chinese)
Citation: You Qi, Zhao Yu, Ma Xiaobinget al. Performance reliability assessment for products based on time series analysis[J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(5): 644-648. (in Chinese)

产品性能可靠性评估的时序分析方法

基金项目: 国家部委基金资助项目(914A19039106HK0108)
详细信息
  • 中图分类号: TB 114.3

Performance reliability assessment for products based on time series analysis

  • 摘要: 针对航空航天产品高可靠性、长寿命的特点,通过综合时序模型对随机序列自拟合性强与短期预测精度高的优点,提出了两类基于性能退化数据的产品可靠性评估时序模型方法.首先,从性能退化量分布的角度出发,在假设退化量分布类型不随时间变化的前提下,利用时间序列建立了性能退化分布参数的分析模型,进而根据可靠度与性能退化量分布的关系进行可靠性评估.然后,从退化轨迹的角度出发,对所有样本的退化轨迹进行时序分析与建模,外推伪失效区间与伪失效寿命值,进而采用完全寿命试验数据的统计方法进行可靠性评估.最后,对某金属材料疲劳裂纹扩展数据进行可靠性评估与寿命预测,结果表明该方法具有良好的稳健性.

     

  • [1] Sun Q, Zhou J L, Zhong Z, et al. Gauss-poisson joint distribution model for degradation failure[J]. IEEE Transactions on Plasma Sciences, 2004, 32(5):1864-1868 [2] Jayaram J S R, Girish T. Reliability prediction through degradation data modeling using a quasi-likelihood approach Proceedings Annual Reliability & Maintainability Symposium. New York: IEEE, 2005:193-199 [3] Huang W, Duane L. An alternative degradation reliability modeling approach maximum likelihood estimation[J]. IEEE Transactions on Reliability, 2005, 54(2):310-317 [4] Wilson S P, Taylor D. Reliability assessment from fatigue micro-crack data[J]. IEEE Transactions on Reliability, 1997, 46(2): 165-171 [5] Eghbali G. Reliability estimate using accelerated degradation data . New Brunswick: Department of Industrial and System Engineering, The State University of New Jersey, 2000 [6] Jiang M X, Zhang Y C. Dynamic modeling of degradation data Proceedings Annual Reliability & Maintainability Symposium. Washington: IEEE, 2002:607-611 [7] 邓爱民, 陈循, 张春华, 等. 基于性能退化数据的可靠性评估[J]. 宇航学报, 2006, 27(3):546-552 Deng Aimin, Chen Xun, Zhang Chunhua, et al. Reliability assessment based on performance degradation data[J]. Journal of Astronautics, 2006, 27(3): 546-552 (in Chinese) [8] Wei Huang, Dietrich D L. An alternative degradation reliability modeling approach using maximum likelihood estimation[J]. IEEE Transactions on Reliability, 2005, 54(2):310-317 [9] 陶庄, 金水高. 时间序列分析简明攻略[J]. 中国卫生统计, 2003, 20(3):151-153 Tao Zhuang, Jin Shuigao. The concise strategy of time series analysis[J].China Health Statistical, 2003, 20(3):151-153 (in Chinese) [10] 张艳, 黄敏, 赵宇, 等. 基于置信分布的系统可靠度评估蒙特卡罗方法[J]. 北京航空航天大学学报, 2006, 32(9):1023-1025 Zhang Yan, Huang Min, Zhao Yu, et al. Monte Carlo method for system reliability evaluation using reliability confidence distribution[J]. Journal of Beijing University of Aeronautics and Astronautics, 2006, 32(9):1024-1025 (in Chinese) [11] Meeker M Q, Escobar L A. Statistical methods for reliability data[M]. New York: John Wiley & Sons, 1998
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出版历程
  • 收稿日期:  2008-08-10
  • 网络出版日期:  2009-05-31

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