摘要
提出基于分层抽样的可靠性灵敏度分析方法。该方法将变量空间分割成多个互斥子空间,根据子空间对可靠性灵敏度估计值贡献率的大小来分配子空间的抽取的样本量,这种抽样策略使得更多的样本来源于失效域,从而达到降低估计方差、提高了收敛速度的目的。本文还推导了基于分层抽样法的可靠性灵敏度估计值的方差和变异系数。三个算例显示出分层抽样在单模式、多模式并联、多模式串联结构可靠性灵敏度分析上的可行性和优越性。
Reliability sensitivity analysis is implemented by the stratified sampling technique in this pa- per. The basic idea of the stratified sampling method can be stated as follows. The random space is divid- ed into many exclusive sub-spaces firstly,and then the number of the samples lying in each sub-space is determined by its~ contribution to the estimator of the reliability sensitivity. More failure samples can be obtained by this strategy than by the crude Monte Carlo simulation. Hence, the corresponding variance of estimator of the reliability sensitivity can be reduced evidently and the convergence rate can be improved remarkably. The expression for the reliability sensitivity, the variance and variation coefficient of the esti- mators are derived in details. Three examples are employed to demonstrate the efficiency and accuracy of the presented approach. The results＇ comparison between the proposed technique and the Monte Carlo method is given. The results show that the presented method can obtain satisfying results with high effi ciency and is versatile for single failure model, serial system, parallel system, etc.
出处
《计算力学学报》
EI
CAS
CSCD
北大核心
2012年第6期841-846,共6页
Chinese Journal of Computational Mechanics
基金
高等学校学科创新引智计划项目(B07050)
西北工业大学基础研究基金(JC20100232)资助项目
