轻工机械2024，Vol.42Issue(4)：7-15,9.DOI:10.3969/j.issn.1005-2895.2024.04.002
基于机器学习的UD布弹道冲击有限元结果分析
Finite Element Results Analysis of UD Fabric Ballistic Impact Based on Machine Learning
摘要
Abstract
Due to the insufficient depth and comprehensiveness of the qualitative comparative observation method currently used to analyze the image results of composite material finite element models,some important information may be overlooked.Therefore,an objective analysis method that can quickly quantify the image is needed.Combined with machine learning,the method of finite element image result analysis based on k-Means clustering algorithm was proposed.Taking the stress distribution results of the ballistic impact finite element model of Dyneema® UD laminate with ordinary aligned stacking and quasi-isotropic stacking as an example,the k-Means clustering algorithm was utilized to cluster and segment the captured stress cloud image by pixel points based on color features.The segmented area enabled fast statistics and area calculations.The results show that this method can efficiently quantify the area difference of different stress ranges,and can obtain more objective and clearer results which is convenient for in-depth analysis.The method can applied to other fields in which cloud image results need to be analyzed.关键词
机器学习/单向织物/k-Means聚类算法/有限元分析/应力分析/弹道冲击Key words
machine learning/UD fabric/k-Means clustering algorithm/FEA(Finite Element Analysis)/stress analysis/ballistic impact分类
机械制造引用本文复制引用
何洁,徐平华,袁子舜,陆振乾,徐望..基于机器学习的UD布弹道冲击有限元结果分析[J].轻工机械,2024,42(4):7-15,9.基金项目
浙江理工大学科研基金(22072134-Y) （22072134-Y）
江苏省高等学校自然科学基金(23KJA430017). （23KJA430017）
