哈尔滨工程大学学报2024，Vol.45Issue(3)：581-589,9.DOI:10.11990/jheu.202206076
机构动作可靠性估计的自适应极值响应面法
An adaptive extremum response surface method for mechanism action reliability estimation
摘要
Abstract
A high-efficiency calculation method based on adaptive extremum response surface(AERS)is proposed to address the problem of mechanism action reliability estimation under random-interval mixed uncertainty.This is then transformed into the problem of solving the upper and lower bounds of action reliability under random uncer-tainty.The mixed kernel extreme learning machine optimized by the sparrow search algorithm is used to construct the initial response surface from mixed uncertainty variables and the extremum response surface(ERS)from the random variables and transform them into the limit state function(LSF)response value and the LSF response extre-mum,respectively.An adaptive infilling strategy combining active learning and opposition-based learning is then used to select the sample points near the limit state surface to update the ERS and thus improve its accuracy and ef-ficiency.Finally,the approximate solutions of the upper and lower bounds of the action reliability are obtained by the ERS and Monte Carlo simulation.The efficiency and accuracy of the proposed method are then verified by a nu-merical case and an engineering case of a rotary chain conveyor.The proposed method provides a reference for the mechanism action reliability estimation under random-interval mixed uncertainty.关键词
动作可靠性/混合不确定性/极值响应面/自适应加点策略/混合核极限学习机/麻雀搜索算法/主动学习/反向学习Key words
action reliability/mixed uncertainty/extremum response surface/adaptive infilling strategy/mixed ker-nel extreme learning machine/sparrow search algorithm/active learning/opposition-based learning分类
军事科技引用本文复制引用
文浩,侯保林..机构动作可靠性估计的自适应极值响应面法[J].哈尔滨工程大学学报,2024,45(3):581-589,9.基金项目
总装备部预研项目(104010401). （104010401）
