Structural Damage Detection Using Parameters Combined with Changes in Flexibility Based on BP Neural Networks

Zhang Jun

doi:10.4028/www.scientific.net/AMR.243-249.5475

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 243-249Structural Damage Detection Using Parameters...

Structural Damage Detection Using Parameters Combined with Changes in Flexibility Based on BP Neural Networks

Abstract:

Modals of BP neural networks with different inputs and outputs are presented for different damage detecting schemes. To identify locations of structural damages, the regular vectors of changes in modal flexibility are looked on as inputs of the networks, and the state of localized damage are as outputs. To identify extents of structural damage, parameters combined with changes in flexibility and the square changes in frequency are as inputs of the networks, and the state of damage extents are as outputs. Examples of a simply supported beam and a plate show that the BP neural network modal can detect damage of structures in quantitative terms.

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Periodical:

Advanced Materials Research (Volumes 243-249)

Pages:

5475-5480

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.243-249.5475

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Online since:

May 2011

Authors:

Zhang Jun

Keywords:

Neural Network (NN), Parameters Combined with Changes in Flexibility, Structural Damage Detection

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