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CRACK IDENTIFICATION USING HYBRID NEURO-GENETIC TECHNIQUE

CRACK IDENTIFICATION USING HYBRID NEURO-GENETIC TECHNIQUE

Authors :
M.-Y. Kim
Myung-Won Suh
Mun-Bo Shim
Source :
Journal of Sound and Vibration. 238:617-635
Publication Year :
2000
Publisher :
Elsevier BV, 2000.

Abstract

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack on a structure, a method is presented in this paper which uses hybrid neuro-genetic technique. Feed-forward multi-layer neural networks trained by back-propagation are used to learn the input (the location and depth of a crack)–output (the structural eigenfrequencies) relation of the structural system. With this trained neural network, genetic algorithm is used to identify the crack location and depth minimizing the difference from the measured frequencies.

Details

ISSN :
0022460X
Volume :
238
Database :
OpenAIRE
Journal :
Journal of Sound and Vibration
Accession number :
edsair.doi...........6b0b2fde3d61d09fb3feae0fc48c7548
Full Text :
https://doi.org/10.1006/jsvi.2000.3089