固体火箭技术2016，Vol.39Issue(1)：106-110,5.DOI:10.7673/j.issn.1006-2793.2016.01.019
一种基于神经网络与粒子群算法辨识针刺炭/炭复合材料弹性常数的方法
Inverse method based on neural network and particle swarm optimization for characterizing the C/C material elastic constants
严博燕 1生志斐 1李耿 1刘芹1
作者信息
- 1. 中国航天科技集团公司四院四十一所，西安 710025
- 折叠
摘要
Abstract
In order to solve the problem of poor precision for measuring C/C composite elastic constant by traditional test meth-od,a new method for obtaining the main elastic constants from modal test was proposed.For plate material,according to the modal test data and the relationship between vibration frequencies and elastic constant,the scope of the elastic constants were estimated preliminarily.Then the neural network model about elastic constants and vibration frequencies was established.At last, use particle swarm optimization to find the optimal solution of the elastic constants. The isotropic and orthotropic thin plates were used to verify this method. and the perfect results were obtained.At last,the elastic constant of needled C/C composite was obtained through the present method. The simulation and experimental results prove that the method is nondestructive,efficient and accurate,and the data of discrete degree is smaller.关键词
针刺炭/炭复合材料/弹性常数/模态试验/神经网络/粒子群算法Key words
needled C/C composite/elastic constants/modal test/neural network/particle swarm optimization分类
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严博燕,生志斐,李耿,刘芹..一种基于神经网络与粒子群算法辨识针刺炭/炭复合材料弹性常数的方法[J].固体火箭技术,2016,39(1):106-110,5.
