Structure Damage Detection Using Neural Network with Multi-Stage Substructuring

2010 ◽  
Vol 13 (1) ◽  
pp. 95-110 ◽  
Author(s):  
Norhisham Bakhary ◽  
Hong Hao ◽  
Andrew J. Deeks
2000 ◽  
Vol 2000.4 (0) ◽  
pp. 343-348
Author(s):  
Jin CHEN ◽  
Xiang SU ◽  
Ichiro HAGIWARA ◽  
Qinzhong SHI

2011 ◽  
Vol 66-68 ◽  
pp. 322-327 ◽  
Author(s):  
Jia Hui ◽  
Xiao Peng Wan ◽  
Mei Ying Zhao

This paper proposed a new method to detect the damage of composite skin/stringer panel structure using modal strain energy combined with neural network. The change ratio of element modal strain energy is choosen as damage indicator because of it’s highly sensitivity to the location and severity of structure damage. Neural network here play the role of a tool to indentity the damage according to the change ratio of modal strain energy. To achive this, a three layers neural network model is built and the BP arithmetic is used. The proposed method is validated using a numerical simulation of a composite skin/stringer panel with damages in some elements of its FEM mode, which are simulated by reducing elements’ material stiffness properties. The result shows that, this method is robust, accurate and highly efficient with the maximal error limited in 10%.


Author(s):  
Guangming Dong ◽  
Jin Chen ◽  
Xuanyang Lei ◽  
Zuogui Ning ◽  
Dongsheng Wang ◽  
...  

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