A novel neural network model of capacitive MEMS accelerometers
This paper presents a nonlinear model for a capacitive Micro-electromechanical 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-Ma...
| 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/69365/1/A%20novel%20neural%20network%20model%20of%20capacitive%20MEMS%20accelerometers.pdf |
| _version_ | 1796978920175697920 |
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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 |
| collection | UPM |
| description | This paper presents a nonlinear model for a capacitive Micro-electromechanical 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 | 2024-03-06T10:01:28Z |
| format | Conference or Workshop Item |
| id | upm.eprints-69365 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:01:28Z |
| publishDate | 2008 |
| publisher | IEEE |
| record_format | dspace |
| spelling | upm.eprints-693652020-07-09T06:36:55Z http://psasir.upm.edu.my/id/eprint/69365/ A novel neural network model of capacitive MEMS accelerometers Bahadorimehr, Alireza Hamidon, Mohd Nizar Hezarjaribi, Yadollah This paper presents a nonlinear model for a capacitive Micro-electromechanical 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/69365/1/A%20novel%20neural%20network%20model%20of%20capacitive%20MEMS%20accelerometers.pdf Bahadorimehr, Alireza and Hamidon, Mohd Nizar and Hezarjaribi, Yadollah (2008) A novel neural network model of capacitive MEMS accelerometers. In: 2008 IEEE International Conference on Semiconductor Electronics (ICSE 2008), 25-27 Nov. 2008, Johor Bahru, Malaysia. (pp. 174-178). 10.1109/SMELEC.2008.4770302 |
| spellingShingle | Bahadorimehr, Alireza Hamidon, Mohd Nizar Hezarjaribi, Yadollah A novel neural network model of capacitive MEMS accelerometers |
| title | A novel neural network model of capacitive MEMS accelerometers |
| title_full | A novel neural network model of capacitive MEMS accelerometers |
| title_fullStr | A novel neural network model of capacitive MEMS accelerometers |
| title_full_unstemmed | A novel neural network model of capacitive MEMS accelerometers |
| title_short | A novel neural network model of capacitive MEMS accelerometers |
| title_sort | novel neural network model of capacitive mems accelerometers |
| url | http://psasir.upm.edu.my/id/eprint/69365/1/A%20novel%20neural%20network%20model%20of%20capacitive%20MEMS%20accelerometers.pdf |
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