机械制造与自动化2025，Vol.54Issue(2)：196-200,232,6.DOI:10.19344/j.cnki.issn1671-5276.2025.02.038
基于Kriging模型的参数不确定性模型修正
Model Updating with Parameter Uncertainty Based on Kriging Model
许泽伟1
作者信息
- 1. 西安铁路职业技术学院,陕西 西安 710026
- 折叠
摘要
Abstract
An uncertainty model updating method is proposed to accurately estimate the probability distribution of parameters and responses,making the model updating more practical.The Latin hypercube sampling method is applied to sample the parameter statistical distance(mean and standard deviation),and the polynomial chaotic expansion model is used to calculate the response statistical distance of each group of sample points.The kriging model is built with the statistical distance of parameters as the input and the statistical distance of structural response as the output,and the functional relationship between parameter uncertainty and response uncertainty is established.The difference between the output of kriging model and the measured data is taken as the objective function,and iterative optimization is conducted by ant lion optimizer algorithm for the optimal solution.The method is verified by 3-DOF spring mass block system and 3-D truss,and the response statistical distance abtained is close to the measured data,which verifies the feasibility of the proposed method.关键词
不确定性模型修正/多项式混沌展开/kriging模型/参数统计矩/蚁狮优化算法Key words
model updating with uncertainty/polynomial chaotic expansion/kriging model/parameter statistical distance/ant lion optimizer algorithm分类
计算机与自动化引用本文复制引用
许泽伟..基于Kriging模型的参数不确定性模型修正[J].机械制造与自动化,2025,54(2):196-200,232,6.
