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基于自适应重要抽样的可靠性分析方法

马纪明 詹晓燕 曾声奎

马纪明, 詹晓燕, 曾声奎等 . 基于自适应重要抽样的可靠性分析方法[J]. 北京航空航天大学学报, 2011, 37(9): 1142-1146,1150.
引用本文: 马纪明, 詹晓燕, 曾声奎等 . 基于自适应重要抽样的可靠性分析方法[J]. 北京航空航天大学学报, 2011, 37(9): 1142-1146,1150.
Ma Jiming, Zhan Xiaoyan, Zeng Shengkuiet al. Reliability analysis method based on adaptive importance sampling[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(9): 1142-1146,1150. (in Chinese)
Citation: Ma Jiming, Zhan Xiaoyan, Zeng Shengkuiet al. Reliability analysis method based on adaptive importance sampling[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(9): 1142-1146,1150. (in Chinese)

基于自适应重要抽样的可靠性分析方法

详细信息
    作者简介:

    马纪明(1979-),男,河南周口人,讲师,jiming.ma@buaa.edu.cn.

  • 中图分类号: TB 114.3

Reliability analysis method based on adaptive importance sampling

  • 摘要: 基于自适应重要抽样(AIS,Adaptive Importance Sampling)的可靠性分析方法,能够克服基于蒙特卡洛方法分析小概率事件时存在的效率低、精度差问题.为解决显性失效方程不存在时寻找失效点困难问题,首先利用条件递归寻找失效点,并使之尽可能在失效面附近;以该失效点为采样中心,抽取失效样本,并不断调整采样中心,使失效样本不断靠近设计点;然后利用这组失效样本估计重要抽样函数的参数,再执行自适应迭代过程,直至失效概率的误差缩小到允许误差限内.最后通过两个典型案例对方法进行应用验证,仿真结果表明在没有失效方程的情况下,能够通过仿真方法很快找到失效点,表明对于不存在显性失效方程的系统,该方法同样适用.与蒙特卡洛方法的对比结果表明该方法在仿真效率上具有较大优越性,且失效概率越小,这种优越性越明显.

     

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出版历程
  • 收稿日期:  2010-04-27
  • 网络出版日期:  2011-09-30

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