Cantilever Beam Natural Frequency Prediction Using Artificial Neural Networks

Sallehuddin Mohamed Haris, Hamed Mohammadi

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Available methods for calculating frequency in cantilever beams have much complexity. In this study we present a new method for calculating natural frequencies in cantilever beams. For this purpose, we use the finite element method (FEM), dynamic analysis and artificial neural network (ANN) techniques to calculate the natural frequency. Finite element software was used to analyze 100 samples of cantilever beams, and the results were used as training and testing data sets in artificial neural networks. For the ANN. the multilayer feed-forward network and back-propagation algorithms were used. We made use of different transfer functions and built 45 different networks in order to find the best network performance. Mean squared error (MSE) was used to evaluate the network performance. Finally, the natural frequencies which were predicted by the ANN techniques were compared to the natural frequencies calculated from theoretical formulation, as well as to those obtained from FEM methods. The results obtained show that the error was quite small.

Original languageEnglish
Title of host publicationLecture Notes in Networks and Systems
PublisherSpringer
Pages441-449
Number of pages9
DOIs
Publication statusPublished - 1 Jan 2018

Publication series

NameLecture Notes in Networks and Systems
Volume16
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Fingerprint

Cantilever beams
Natural frequencies
Neural networks
Network performance
Finite element method
Backpropagation algorithms
Dynamic analysis
Transfer functions
Multilayers
Testing

Keywords

  • Artificial neural networks
  • Cantilever beams
  • Finite elements
  • Mean squared error
  • Natural frequency

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Control and Systems Engineering

Cite this

Mohamed Haris, S., & Mohammadi, H. (2018). Cantilever Beam Natural Frequency Prediction Using Artificial Neural Networks. In Lecture Notes in Networks and Systems (pp. 441-449). (Lecture Notes in Networks and Systems; Vol. 16). Springer. https://doi.org/10.1007/978-3-319-56991-8_33

Cantilever Beam Natural Frequency Prediction Using Artificial Neural Networks. / Mohamed Haris, Sallehuddin; Mohammadi, Hamed.

Lecture Notes in Networks and Systems. Springer, 2018. p. 441-449 (Lecture Notes in Networks and Systems; Vol. 16).

Research output: Chapter in Book/Report/Conference proceedingChapter

Mohamed Haris, S & Mohammadi, H 2018, Cantilever Beam Natural Frequency Prediction Using Artificial Neural Networks. in Lecture Notes in Networks and Systems. Lecture Notes in Networks and Systems, vol. 16, Springer, pp. 441-449. https://doi.org/10.1007/978-3-319-56991-8_33
Mohamed Haris S, Mohammadi H. Cantilever Beam Natural Frequency Prediction Using Artificial Neural Networks. In Lecture Notes in Networks and Systems. Springer. 2018. p. 441-449. (Lecture Notes in Networks and Systems). https://doi.org/10.1007/978-3-319-56991-8_33
Mohamed Haris, Sallehuddin ; Mohammadi, Hamed. / Cantilever Beam Natural Frequency Prediction Using Artificial Neural Networks. Lecture Notes in Networks and Systems. Springer, 2018. pp. 441-449 (Lecture Notes in Networks and Systems).
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