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...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2008
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| Online Access: | http://psasir.upm.edu.my/id/eprint/69349/ http://psasir.upm.edu.my/id/eprint/69349/1/Nonlinear%20modeling%20of%20a%20capacitive%20MEMS%20accelerometer%20using%20neural%20network.pdf |
| _version_ | 1848856382346887168 |
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| author | Bahadorimehr, Alireza Hamidon, Mohd Nizar Hezarjaribi, Yadollah |
| author_facet | Bahadorimehr, Alireza Hamidon, Mohd Nizar Hezarjaribi, Yadollah |
| author_sort | Bahadorimehr, Alireza |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T11:40:46Z |
| format | Conference or Workshop Item |
| id | upm-69349 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:40:46Z |
| publishDate | 2008 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| spellingShingle | Bahadorimehr, Alireza Hamidon, Mohd Nizar Hezarjaribi, Yadollah Nonlinear modeling of a capacitive MEMS accelerometer using neural network |
| title | 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_short | Nonlinear modeling of a capacitive MEMS accelerometer using neural network |
| title_sort | nonlinear modeling of a capacitive mems accelerometer using neural network |
| url | http://psasir.upm.edu.my/id/eprint/69349/ http://psasir.upm.edu.my/id/eprint/69349/ http://psasir.upm.edu.my/id/eprint/69349/1/Nonlinear%20modeling%20of%20a%20capacitive%20MEMS%20accelerometer%20using%20neural%20network.pdf |