Title :
A Novel Neural Network Model of Capacitive MEMS Accelerometers
Author :
Bahadorimehr, A.R. ; Hamidon, M.N. ; Hezarjaribi, Y.
Author_Institution :
Electr. & Electron. Dept., Univ. Putra Malaysia, Serdang
Abstract :
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.
Keywords :
accelerometers; capacitive sensors; computerised instrumentation; finite element analysis; learning (artificial intelligence); microsensors; neural nets; FEA method; Levenberg-Marquardt method; capacitive MEMS accelerometer; folded-flexure spring; microelectromechanical accelerometer; neural network model; nonlinear model; Acceleration; Accelerometers; Circuits; Damping; Electrostatics; Fingers; Micromechanical devices; Neural networks; Nonlinear equations; Springs;
Conference_Titel :
Semiconductor Electronics, 2008. ICSE 2008. IEEE International Conference on
Conference_Location :
Johor Bahru
Print_ISBN :
978-1-4244-3873-0
Electronic_ISBN :
978-1-4244-2561-7
DOI :
10.1109/SMELEC.2008.4770302
