摘要
针对随机和模糊混合不确定性下利用传统蒙特卡洛方法进行可靠性分析效率低的问题,提出了一种基于λ截集和改良的先进均值法的可靠性分析方法,该方法首先基于概率论和可能性理论建立了混合不确定性下的可靠性分析模型,然后利用先进均值法进行概率可靠性分析,利用λ截集优化法进行不同截集下的可能性分析。通过概率分析和可能性分析的迭代循环求解概率、模糊混合不确定性下的可靠性分析结果。最后的算例证明该方法在保证求解精度的同时,可以有效地提高混合不确定性下的可靠性分析效率。
In order to solve the poor efficiency problem of reliability analysis using Monte Carlo method under the stochastic and fuzzy uncertainty, a reliability calculation method based on λ-cut and Modified Advanced Mean Value (MAMV) is proposed to balance the precision and efficiency of reliability solution with mixed uncertainty. Firstly, a unified reliability analysis model is established. Then, the proposed method ,which uses the MAMV method to execute the probability analysis and uses theλ-cut method to carry on the possibility analysis, is used to solve the reliability problem with mixed uncertainties by a iteration loop of possibility analysis and probability analysis. At the end, a example is present to prove the validity of the method. The results show that the proposed method can effectively improve the reliability analysis efficiency under the mixed uncertainties.
出处
《机械设计与制造》
北大核心
2017年第S1期225-228,共4页
Machinery Design & Manufacture
基金
国家自然科学基金(61203181)
关键词
随机不确定性
模糊不确定性
可靠性分析
λ截集
改良的先进均值法
Aleatory Uncertainty
Fuzzy Uncertainty
Mixed Uncertainty
Reliability Analysis
λ-Cut
Modified Ad-vanced Mean Value