DocumentCode :
3354994
Title :
Damage identification and simulation of structure based on RBF network
Author :
Jianwei, Zhang ; Yina, Zhang
Author_Institution :
North China Univ. of Water Conservancy & Electr. Power, Zhengzhou, China
fYear :
2010
fDate :
26-28 June 2010
Firstpage :
1608
Lastpage :
1610
Abstract :
RBF neural network is presented to identify and locate the crack damage of concrete structures in this paper. A cantilever is analyzed by finite element method, and the damage indices of the perfect structure and damaged structure are gained. Then RBF neural network is used to analyze the single damage and multi-damage quantification and damage location. Numerical simulation results show that RBF neural network method can make a better diagnosis for single and multiple damage identification. This method has certain guiding sense to damage identification in actual structures.
Keywords :
cantilevers; condition monitoring; crack detection; finite element analysis; radial basis function networks; structural engineering; RBF neural network; cantilever; concrete structures; crack damage; damage identification; damage location; finite element method; multidamage quantification; structure simulation; Artificial neural networks; Civil engineering; Frequency; Kernel; Multi-layer neural network; Neural networks; Pattern recognition; Radial basis function networks; Rivers; Water conservation; RBF neural network; damage identification; simulation analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7737-1
Type :
conf
DOI :
10.1109/MACE.2010.5535986
Filename :
5535986
Link To Document :
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