摘要
为合理衡量不确定性因素对撒砂装置最大应力的影响,提升其稳健可靠性水平,文中提出了基于多权值优化代理模型的稳健可靠性设计方法。首先,构建撒砂装置有限元模型并计算其最大应力响应;其次,提取不确定性因素并编制参数化分析文件,进而依据试验设计结果,初步构建不确定性因素与最大应力的代理模型,采用遗传算法对代理模型中传递及加权系数进行优化,提升代理模型对最大应力响应预测结果的合理性;最后,基于稳健可靠性设计思想,建立撒砂装置稳健可靠性优化设计模型,并通过对比分析验证所提方法的有效性。结果表明:多权值优化代理模型最大应力决定系数提升至0.9918;经稳健可靠性设计得到的撒砂装置最大应力波动标准差减小至1.46 MPa,可为其他工程结构稳健可靠性的设计提供一定参考。
In this article,in order to reasonably measure the influence of uncertainty factors on the maximum stress of the sanding device and improve its robust reliability,the multi-weight optimization agent model is used to design the robust reliability.Firstly,the finite-element model of the sanding device is constructed and its maximum stress response is calculated.Secondly,the uncertainty factors are extracted and the parametric analysis documents are compiled;then,according to the test design results,the proxy model of the uncertainty factors and the maximum stress is preliminarily set up.The genetic algorithm is used to optimize the transfer and the weighting coefficients in the proxy model,so as to improve the rationality of the proxy model in predicting the maximum stress response.Finally,based on the concept of the robust reliability design,the optimization design model of the sanding device is established,and the comparative analysis is carried out to verify whether this method is effective.The results show that the maximum stress determination coefficient of the multi-weight optimization proxy model increases to 0.9918.The standard deviation of the maximum stress fluctuation of the sanding device obtained from the robust reliability design reduces to 1.46 MPa.This study provides reference for the robust reliability design of other engineering structures.
作者
李云全
曹阳
智鹏鹏
毋高峰
LI Yunquan;CAO Yang;ZHI Pengpeng;WU Gaofeng(Jiaozuo Normal College,Jiaozuo 454000;CRRC Nanjing Puzhen Co.,Ltd.,Nanjing 210031;Yangtze Delta Region Institute(Huzhou),University of Electronic Science and Technology of China,Huzhou 313001;Institute of Electronic and Information Engineering in Guangdong,University of Electronic Science and Technology of China,Donggu)
出处
《机械设计》
CSCD
北大核心
2023年第8期113-120,共8页
Journal of Machine Design
基金
广东省基础与应用基础研究基金项目(2021A1515110308)。
关键词
撒砂装置
稳健可靠性
优化设计
BP神经网络
遗传算法
sanding device
robust reliability
optimization design
BP neural network
genetic algorithm
