Design and Analysis of MEMS Pressure Transmitter Using Mach–Zehnder Interferometer and Artificial Neural Networks
Micro-electro mechanical systems (MEMS) designing is used to produce component having very small dimensions. In this paper, MEMS-based pressure sensors working using the capacitive sensing technique are worked upon. Furthermore, using neural networks the voltage output produced is linearized. This decreases the non-linearity error. One possible limitation of this electrical circuit is the inability to be used in high temperature regions. This limitation has been overcome by implementing an electro-optic technique by means of which the electrical signal is converted to optical signal. This novelty does not only give the added benefit of being able to be used in inflammable regions but also eases transmission in remote locations. This is done by Mach–Zehnder interferometer whose simulations of intensity variation are studied using OptiBPM software.