Neural network study of two proposed structures: 1. Truncated conical monopole: 2. Fan-Beam structure fed by a metal-dielectric feeder

Author(s):  
Chinmoy Das Gupta ◽  
R. Badlishah bin Ahmad ◽  
Ir Anuar Mat Safar ◽  
Azremi Abdullah Al-Hadi
2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Bo Yan ◽  
Yao Cui ◽  
Lin Zhang ◽  
Chao Zhang ◽  
Yongzhi Yang ◽  
...  

It is not easy to find marine cracks of structures by directly manual testing. When the cracks of important components are extended under extreme offshore environment, the whole structure would lose efficacy, endanger the staff’s safety, and course a significant economic loss and marine environment pollution. Thus, early discovery of structure cracks is very important. In this paper, a beam structure damage identification model based on intelligent algorithm is firstly proposed to identify partial cracks in supported beams on ocean platform. In order to obtain the replacement mode and strain mode of the beams, the paper takes simple supported beam with single crack and double cracks as an example. The results show that the difference curves of strain mode change drastically only on the injured part and different degrees of injury would result in different mutation degrees of difference curve more or less. While the model based on support vector machine (SVM) and BP neural network can identify cracks of supported beam intelligently, the methods can discern injured degrees of sound condition, single crack, and double cracks. Furthermore, the two methods are compared. The results show that the two methods presented in the paper have a preferable identification precision and adaptation. And damage identification based on support vector machine (SVM) has smaller error results.


Author(s):  
Venicio Silva Araujo ◽  
Guilherme Silva Prado ◽  
Heinsten Frederich Leal dos Santos

2000 ◽  
Vol 25 (4) ◽  
pp. 325-325
Author(s):  
J.L.N. Roodenburg ◽  
H.J. Van Staveren ◽  
N.L.P. Van Veen ◽  
O.C. Speelman ◽  
J.M. Nauta ◽  
...  

2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document