Research on delamination monitoring for composite structures based on HHGA-WNN
Research on delamination monitoring for composite structures based on HHGA-WNN
复制标题
基于HHGA-WNN的复合材料结构分层监测研究
DOI：
10.1016/j.asoc.2008.11.008
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发表时间：
2009-06
影响因子：
8.7
通讯作者：
Zheng, Shi-jie
中科院分区：
文献类型：
--
作者：
Wang, Hong-tao;Li, Zheng-qiang;Zheng, Shi-jie
Due to the deficiencies of the training algorithms for available wavelet neural network used for structural health monitoring, a new hybrid hierarchy genetic algorithm was introduced by combining hierarchy genetic algorithm and least-square method to improve the learning procedure of wavelet neural network. The hybrid algorithm was able to determine the structure and parameters of the wavelet neural network simultaneously. In this algorithm, adaptive crossover and mutation probability were used to accelerate the genetic speed and avoid the occurrence of prematurity. The modal frequencies of a glass/epoxy laminates beam with varying assumed delamination sizes and locations were computed using finite element method and fed into the wavelet neural network to predict the delamination location and its extent. The simulation demonstrates that the wavelet neural network based on hybrid hierarchy genetic algorithm is robust, promising and converges very fast.
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影响因子：
4.7
作者：
Y. Zou;L. Tong;G. Steven
通讯作者：
Y. Zou;L. Tong;G. Steven
影响因子：
4.1
作者：
Shijie Zheng;Xinwei Wang;Wanji Chen
通讯作者：
Shijie Zheng;Xinwei Wang;Wanji Chen
DOI：
10.1109/iecon.1997.664911
发表时间：
1997-01
期刊：
Proceedings of the IECON'97 23rd International Conference on Industrial Electronics, Control, and Instrumentation (Cat. No.97CH36066)
影响因子：
--
作者：
K.F. Man;K. Tang
通讯作者：
K.F. Man;K. Tang
影响因子：
4.5
作者：
R. Tabaraki;T. Khayamian;A. Ensafi
通讯作者：
R. Tabaraki;T. Khayamian;A. Ensafi
影响因子：
--
作者：
Qinghua Zhang
通讯作者：
Qinghua Zhang