Damage Severity Assessment Using Modified BP Neural Network

Abstract:

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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.

Info:

Periodical:

Advanced Materials Research (Volumes 179-180)

Edited by:

Garry Zhu

Pages:

1016-1020

DOI:

10.4028/www.scientific.net/AMR.179-180.1016

Citation:

X. M. Dong and Z. H. Wang, "Damage Severity Assessment Using Modified BP Neural Network", Advanced Materials Research, Vols. 179-180, pp. 1016-1020, 2011

Online since:

January 2011

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Price:

$35.00

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