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Nonlinear modeling of a capacitive MEMS accelerometer using neural network

This paper presents a nonlinear model for a capacitive Microelectromechanical accelerometer (MEMA). System parameters of the accelerometer are developed using the effect of cubic term of the folded-flexure spring. To solving this equation we use FEA method. The neural network (NN) uses Levenberg-Mar...

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Main Authors: Bahadorimehr, Alireza, Hamidon, Mohd Nizar, Hezarjaribi, Yadollah
Format: Conference or Workshop Item
Language:English
Published: IEEE 2008
Online Access:http://psasir.upm.edu.my/id/eprint/69349/1/Nonlinear%20modeling%20of%20a%20capacitive%20MEMS%20accelerometer%20using%20neural%20network.pdf
http://psasir.upm.edu.my/id/eprint/69349/
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spelling my.upm.eprints.693492020-07-09T06:38:27Z http://psasir.upm.edu.my/id/eprint/69349/ Nonlinear modeling of a capacitive MEMS accelerometer using neural network Bahadorimehr, Alireza Hamidon, Mohd Nizar Hezarjaribi, Yadollah This paper presents a nonlinear model for a capacitive Microelectromechanical accelerometer (MEMA). System parameters of the accelerometer are developed using the effect of cubic term of the folded-flexure spring. To solving this equation we use FEA method. The neural network (NN) uses Levenberg-Marquardt (LM) method for training the system to have more accurate response. The designed NN can identify and predict the displacement of movable mass of accelerometer. The simulation results are very promising. IEEE 2008 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/69349/1/Nonlinear%20modeling%20of%20a%20capacitive%20MEMS%20accelerometer%20using%20neural%20network.pdf Bahadorimehr, Alireza and Hamidon, Mohd Nizar and Hezarjaribi, Yadollah (2008) Nonlinear modeling of a capacitive MEMS accelerometer using neural network. In: 33rd IEEE/CPMT International Electronics Manufacturing Technology Conference (IEMT 2008), 4-6 Nov. 2008, Penang, Malaysia. (pp. 1-6). 10.1109/IEMT.2008.5507887
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This paper presents a nonlinear model for a capacitive Microelectromechanical accelerometer (MEMA). System parameters of the accelerometer are developed using the effect of cubic term of the folded-flexure spring. To solving this equation we use FEA method. The neural network (NN) uses Levenberg-Marquardt (LM) method for training the system to have more accurate response. The designed NN can identify and predict the displacement of movable mass of accelerometer. The simulation results are very promising.
format Conference or Workshop Item
author Bahadorimehr, Alireza
Hamidon, Mohd Nizar
Hezarjaribi, Yadollah
spellingShingle Bahadorimehr, Alireza
Hamidon, Mohd Nizar
Hezarjaribi, Yadollah
Nonlinear modeling of a capacitive MEMS accelerometer using neural network
author_facet Bahadorimehr, Alireza
Hamidon, Mohd Nizar
Hezarjaribi, Yadollah
author_sort Bahadorimehr, Alireza
title Nonlinear modeling of a capacitive MEMS accelerometer using neural network
title_short Nonlinear modeling of a capacitive MEMS accelerometer using neural network
title_full Nonlinear modeling of a capacitive MEMS accelerometer using neural network
title_fullStr Nonlinear modeling of a capacitive MEMS accelerometer using neural network
title_full_unstemmed Nonlinear modeling of a capacitive MEMS accelerometer using neural network
title_sort nonlinear modeling of a capacitive mems accelerometer using neural network
publisher IEEE
publishDate 2008
url http://psasir.upm.edu.my/id/eprint/69349/1/Nonlinear%20modeling%20of%20a%20capacitive%20MEMS%20accelerometer%20using%20neural%20network.pdf
http://psasir.upm.edu.my/id/eprint/69349/
_version_ 1672612205985529856
score 13.209306

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