EngineeringMaterials ScienceComputer Science
DOI: 10.1006/jsvi.2000.3089

tlooto Summary

To identify the location and depth of a crack in a structure, a method is presented in this paper which uses hybrid neuro-genetic technique and genetic algorithm to fine the minimum square error.

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 in a structure, a method is presented in this paper which uses hybrid neuro-genetic technique. Feed-forward multilayer neural networks trained by back-propagation are used to learn the input)the location and dept of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this neural network and genetic algorithm, it is possible to formulate the inverse problem. Neural network training algorithm is the back propagation algorithm with the momentum method to attain stable convergence in the training process and with the adaptive learning rate method to speed up convergence. Finally, genetic algorithm is used to fine the minimum square error.

Citation format

SUH, M.; SHIM, Mun-Bo. Crack identification using hybrid neuro-genetic technique. Journal of the Korean Society for Precision Engineering, 2000, 16: 158–165.