Damage Severity Assessment Using Modified BP Neural Network

Article Preview

Abstract:

Damage severity identification is an important content among structural damage identification. In order to avoid the disadvantages of conventional BPNN, a modified BP neural network was proposed to identify structural damage severity in this paper. The modified BPNN was trained by using structural modal frequency qua BPNN input, and then used to forecast structural damage severity. Finally, the results of simulation experiment of composite material cantilever girder show that the improved method is very effective for damage severity identification and possess great applied foreground.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 179-180)

Pages:

1016-1020

Citation:

Online since:

January 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Anjan Dutta, S. Talukdar. Damage detection in bridges using accurate modal parameters. Finite Elements in Analysis and Design, 2004, 40: 287~304.

DOI: 10.1016/s0168-874x(02)00227-5

Google Scholar

[2] Zhao J, Ivan J N, DeWolf J T. Structural damage detection using artificial neural networks. J. Infrastruct. Syst., ASCE. 1998, 4: 93~101.

DOI: 10.1061/(asce)1076-0342(1998)4:3(93)

Google Scholar

[3] Worden K. Structural fault detection using a novelty measure. Journal of Sound and Vibration, 1997, 2001(1): 85~101.

DOI: 10.1006/jsvi.1996.0747

Google Scholar

[4] Wu X, Ghaboussi J, Garrett J.H. Use of neural networks in detection of structural damage. Computers & Structures. 1992, 42: 649~659.

DOI: 10.1016/0045-7949(92)90132-j

Google Scholar

[5] Elkordy M F, Chang K C, Lee G C. Neural networks trained by analytically simulated damage states. Journal of Computing in Civil Engineering, ASCE. 1993, 7: 130~145.

DOI: 10.1061/(asce)0887-3801(1993)7:2(130)

Google Scholar

[6] Barai S V, Pandey P C. Vibration signature analysis using artifical networks. J. Computing in Civ. Engrg. , ASCE. 1995, 9: 259~265.

Google Scholar

[7] Tsou P, Shen M-H H. Structural damage detection and identification using neural networks. AIAA Journal. 1994, 32: 176~183.

DOI: 10.2514/3.11964

Google Scholar

[8] Zhao J, Ivan J N, DeWolf J T. Structural damage detection using artificial neural networks. J. Infrastruct. Syst., ASCE. 1998, 4: 93~101.

DOI: 10.1061/(asce)1076-0342(1998)4:3(93)

Google Scholar