Pull-in Phenomenon in the Electrostatically Micro-switch Suspended between Two Conductive Plates using the Artificial Neural Network

Mortaza Aliasghary, Hamed Mobki*, Hassen M. Ouakad

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Artificial Neural Networks (ANN) are designed to evaluate the pull-in voltage of MEMS switches. The mathematical model of a micro-switch subjected to electrostatic force is preliminarily illustrated to get the relevant equations providing static deflection and pull-in voltage. Adopting the Step-by-Step Linearization Method together with a Galerkin-based reduced order model, numerical results in terms of pull-in voltage are obtained to be employed in the training process of ANN. Then, feed forward back propagation ANNs are designed and a learning process based on the Levenberg-Marquardt method is performed. The ability of designed neural networks to determine pull-in voltage have been compared with previous results presented in experimental and theoretical studies and it has been shown that the presented method has a good ability to approximate the threshold voltage of micro switch. Furthermore, the geometric and physical effect of the micro-switch on the pull-in voltage was also examined using these designed networks and relevant findings were provided.

Original languageEnglish
Pages (from-to)1222-1235
Number of pages14
JournalJournal of Applied and Computational Mechanics
Volume8
Issue number4
DOIs
Publication statusPublished - 2022

Keywords

  • Artificial neural network.
  • Electrostatic
  • Mems
  • Pull-in instability

ASJC Scopus subject areas

  • Computational Mechanics
  • Mechanical Engineering

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