Nonlinear modeling of a capacitive MEMS accelerometer using neural network

Citation

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).

Abstract

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.

Download File

Preview

Text (Abstract)
Nonlinear modeling of a capacitive MEMS accelerometer using neural network.pdf
Download (34kB) | Preview

Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Engineering
DOI Number:	https://doi.org/10.1109/IEMT.2008.5507887
Publisher:	IEEE
Keywords:	Nonlinear model; Neural network; Capacitive MEMA
Depositing User:	Nabilah Mustapa
Date Deposited:	04 Jul 2019 03:47
Last Modified:	09 Jul 2020 06:38
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/IEMT.2008.5507887
URI:	http://psasir.upm.edu.my/id/eprint/69349
Statistic Details:	View Download Statistic

Actions (login required)

View Item