Estimation of Uncertainty in the Lateral Vibration Attenuation of a Beam with Piezo-Elastic Supports by Neural Networks

Benedict Götz; Sebastian Kersting

doi:10.4028/www.scientific.net/AMM.885.293

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 885Estimation of Uncertainty in the Lateral Vibration...

Estimation of Uncertainty in the Lateral Vibration Attenuation of a Beam with Piezo-Elastic Supports by Neural Networks

Abstract:

Quantification of uncertainty in technical systems is often based on surrogate models of corresponding simulation models. Usually, the underlying simulation model does not describe the reality perfectly, and consequently the surrogate model will be imperfect.In this article we propose an improved surrogate model of the vibration attenuation of a beam with shunted piezoelectric transducers. Therefore, experimentally observed and simulated variations in the vibration attenuation are combined in the model estimation process, by using multi--layer feedforward neural networks. Based on this improved surrogate model, we construct a density estimate of the maximal amplitude in the vibration attenuation.The density estimate is used to analyze the uncertainty in the vibration attenuation, resulting from manufacturing variations.

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Uncertainty in Mechanical Engineering III

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Periodical:

Applied Mechanics and Materials (Volume 885)

Pages:

293-303

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.885.293

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Online since:

November 2018

Authors:

Benedict Götz*, Sebastian Kersting

Keywords:

Density Estimation, Imperfect Model, Neural Network, Surrogate Model, Uncertainty Quantification

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Creative Commons CC BY 4.0

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* - Corresponding Author

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