Stiffness parameter prediction for elastic supports of non-uniform rods

Authors

DOI:

https://doi.org/10.12697/ACUTM.2024.28.08

Keywords:

non-uniform rods, free vibration, Haar wavelet, backpropagation network, random forest

Abstract

The present research focuses on establishing the stiffness parameter of elastic springs placed at the ends of non-uniform rods. The governing equation for the longitudinal vibrations of the rod was solved using the Haar wavelet integration method. The calculated natural frequency parameters closely aligned with those available in the literature. The normalised values of the first ten natural frequency parameters were used in the feature vector to predict the stiffness parameter of the springs. A feedforward neural network with two hidden layers made accurate predictions when the range of each natural frequency parameter
within its domain exceeded one. The insights garnered from this study contribute to the design, optimisation and assessment of diverse engineering applications.

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Author Biographies

Ljubov Jaanuska, University of Tartu

Department of Computer Science

Helle Hein, University of Tartu

Department of Computer Science

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Published

2024-06-03

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Section

Articles