基于BP神经网络的木芯复合材料结构疲劳寿命预测
Fatigue life prediction of wood core composite sandwich structure based on the bp neural network
徐子恒 1史慧媛 1方海 2祝典 2夏志远 1唐柏鉴1
作者信息
- 1. 苏州科技大学土木工程学院,江苏苏州 215011
- 2. 南京工业大学土木工程学院,江苏南京 211800
- 折叠
摘要
以不同试验条件下木芯复合材料结构的三点弯曲疲劳试验和四点弯曲疲劳试验的疲劳试验数据为样本,构建载荷等级-疲劳寿命(S-N)曲线模型和BP神经网络模型,并对试件疲劳寿命进行预测,同时利用BP神经网络对木芯复合材料结构疲劳寿命影响因素进行权重分析.结果表明:指数函数模型、幂函数模型、BP神经网络模型均可有效实现对木芯复合材料结构的疲劳寿命预测,其中BP神经网络模型的预测精度最高;载荷等级、均质化格构腹板面积比、跨高比对疲劳寿命的影响权重依次降低,合理设置格构腹板是提高木芯复合材料结构疲劳寿命的有效方法之一.
Abstract
Taking the fatigue test data from three-point and four-point bending fatigue tests of wood core composite sandwich structures under various experimental conditions as samples,constructed the load level-fatigue life(S-N)curve model and the BP neural network model to predict the fatigue life of the specimens.Additionally,the BP neural network was utilized to perform a weight analysis on the factors influencing the fatigue life of the wood core composite sandwich structures.The results indicate that the exponential function model,power function model,and BP neural network model can all effectively predict the fatigue life of the wood core composite sandwich structures,with the BP neural network model demonstrating the highest predictive accuracy.The influence of the load level,homogenized grid web area ratio,and span-to-height ratio on fatigue life decreases sequentially.Configuring the lattice webs is one of the effective methods to enhance the fatigue life of wood core composite sandwich structures.
关键词
木芯复合材料结构/疲劳寿命预测/S-N曲线/BP神经网络Key words
wood core composite structure/fatigue life prediction/S-N curve/BPNN引用本文复制引用
基金项目
国家自然科学基金(52108236)
国家自然科学基金(52208188)
江苏省自然科学基金(BK20200986)
出版年
2024
国家科技期刊平台
NSTL
万方数据