南京航空航天大学学报2018，Vol.50Issue(1)：30-35,6.DOI:10.16356/j.1005-2615.2018.01.005
复合材料低速冲击损伤面积神经网络估算方法
Estimation Method for Damage Area After Low-Velocity Impact of Composite Material Based on Neural Network
摘要
Abstract
The damage area is one of the main characterization parameters of the extent of the damage in the composite laminates after the low-velocity impact.Based on the BP artificial neural network of three-layer topological structure,this paper establishes a rapid estimation model of damage area with the im-pact energy and the depth of indentation as input parameters.After training the BP neural network model with the test sample data,other sample data are simulated and verified.Through the comparative analysis,it is considered that the damage area estimation model has sufficient generalization ability of experimental data,and its estimation accuracy and efficiency can fulfill the requirements.It provides a new and effective method for estimating the damage area of composite laminates after low-velocity impact.关键词
复合材料/低速冲击/损伤面积/估算Key words
composite/low-velocity impact/damage area/estimation分类
通用工业技术引用本文复制引用
盛鸣剑,陈普会..复合材料低速冲击损伤面积神经网络估算方法[J].南京航空航天大学学报,2018,50(1):30-35,6.基金项目
国家自然科学基金(11572152)资助项目 （11572152）
江苏省高校优势学科建设工程资助项目. （）
