Identifying Damage of the Benchmark Structure by Using Artificial Neural Network Methods

Abstract:

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This paper discusses the damage identification using artificial neural network methods for the benchmark problem set up by IASC-ASCE Task Group on Health Monitoring. A three-stage damage identification strategy for building structures is proposed. The BP network and PNN are employed for damage localization and BP network for damage extent identification. Four damage patterns (patterns i~iv) in Cases 1-6 are discussed. The comparison between BP network and PNN are carried out. The results show that PNN performs better than BP network in damage localization. The damage extent identification using BPN is successful even in Cases 2 and 5&6 in which the modeling error is quite large.

Info:

Periodical:

Advanced Materials Research (Volumes 219-220)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

312-317

DOI:

10.4028/www.scientific.net/AMR.219-220.312

Citation:

B. S. Wang "Identifying Damage of the Benchmark Structure by Using Artificial Neural Network Methods", Advanced Materials Research, Vols. 219-220, pp. 312-317, 2011

Online since:

March 2011

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Price:

$35.00

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