Damage Identification of Simply Supported Bridge Based On RBF Neural Network

被引：0
|
作者：
Liu, Hanbing [1 ]
Jiao, Yubo [1 ]
机构：
[1] Jilin Univ, Coll Transportat, Changchun 130023, Peoples R China
来源：
INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2012) | 2013年 / 8768卷
关键词：
Simply supported bridge with multiple girders; Damage identification; Curvature modal shape; RBF neural networks; Contrast analysis;
D O I：
10.1117/12.2010758
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
Efficient non-destructive damage detection procedures for bridge structures have become an important research topic. In this paper, the damage location is detected using modal shape curvature, while the damage severity is identified based on RBF neural network. A numerical example for a simply supported beam bridge with five girders is provided to verify the feasibility of the method. The contrast analysis between RBF and BP neural networks is conducted to confirm the superiority of RBF network. The results shown that the convergence speed of RBF is faster than BP, and the RBF network also possesses more favorable damage identification results.
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页数：7
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