Share Email Print
cover

Proceedings Paper

Damage identification of simply supported bridge based on RBF neural network
Author(s): Hanbing Liu; Yubo Jiao
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

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.

Paper Details

Date Published: 14 March 2013
PDF: 7 pages
Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87681B (14 March 2013); doi: 10.1117/12.2010758
Show Author Affiliations
Hanbing Liu, Jilin Univ. (China)
Yubo Jiao, Jilin Univ. (China)


Published in SPIE Proceedings Vol. 8768:
International Conference on Graphic and Image Processing (ICGIP 2012)
Zeng Zhu, Editor(s)

© SPIE. Terms of Use
Back to Top