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一种基于自适应Kriging集成模型的结构可靠性分析方法

高进 崔海冰 樊涛 李昂 杜尊峰

中国机械工程2024,Vol.35Issue(1):83-92,10.
中国机械工程2024,Vol.35Issue(1):83-92,10.DOI:10.3969/j.issn.1004-132X.2024.01.008

一种基于自适应Kriging集成模型的结构可靠性分析方法

A Structural Reliability Calculation Method Based on Adaptive Kriging Ensemble Model

高进 1崔海冰 1樊涛 2李昂 2杜尊峰2

作者信息

  • 1. 潍柴动力股份有限公司,潍坊,261061||内燃机可靠性国家重点实验室,潍坊,261061
  • 2. 天津大学建筑工程学院,天津,300354
  • 折叠

摘要

Abstract

The reliability analysis results of complex structures based on the Kriging model were highly dependent on the fitting accuracy of the Kriging model.In the constructing processes of the Kriging model,the selection of different correlation and regression functions affected the accuracy of the model.In order to solve the impacts of model uncertainty on the reliability analysis results,while considering computational efficiency and accuracy,based on the Kriging model and Monte Carlo simu-lation(MCS)method,a structural reliability calculation method combining adaptive ensemble strategy and active learning function was proposed.Considering the modeling uncertainty of Kriging models,combined with multiple Kriging models,this methed constructed an active learning function that com-prehensively considered sample point contribution and sample point distance.The ensemble Kriging model was iteratively updated through the active learning function until the convergence conditions were satisfied.Finally the structural reliability analysis was carried out by the constructed ensemble Kriging model and MCS method.The validity of the proposed method was verified by numerical and engineering examples,and the results show that the proposed method is more robust than other major methods,and the computational efficiency is higher while ensuring the computational accuracy.

关键词

结构可靠性/自适应集成策略/Kriging模型/主动学习函数

Key words

structural reliability/adaptive ensemble strategy/Kriging model/active learning function

分类

机械制造

引用本文复制引用

高进,崔海冰,樊涛,李昂,杜尊峰..一种基于自适应Kriging集成模型的结构可靠性分析方法[J].中国机械工程,2024,35(1):83-92,10.

基金项目

内燃机可靠性国家重点实验室开放课题(skler-202112) (skler-202112)

中国机械工程

OA北大核心CSTPCD

1004-132X

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