Dynamic model updating using neural networks

Leonard Ziemiański; Bartosz Miller

Leonard Ziemiański Rzeszów University of Technology
Bartosz Miller Rzeszów University of Technology

Abstract

The paper presents an application of Artificial Neural Networks for updating a mathematical model of the structure based on dynamic parameters. Neural networks which predict the value of selected stiffness or concentrated masses on the basis of Frequency Response Function (FRF) have been built. Two types of neural networks have been used for this task: multi-layer feed-forward (MLFF) networks with different learning algorithms and networks with radial basis function (RBF). Preceding the update, the FRF is compressed in order to reduce the number of input values necessary for updating the model.

Keywords

References

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Dynamic model updating using neural networks

Abstract

Keywords

References

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