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Design, simulation and optimization of micro Pressure sensors

Meenatchisundaram, S (2014) Design, simulation and optimization of micro Pressure sensors. Phd. Thesis thesis, Manipal Institute of Technology.

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Abstract

New and improved methods of sensor design are constantly being developed over the years. As technology grows up, the challenges faced by design engineers are also increasing drastically. Micro pressure sensors have captured their market because of their wide range of application from very low to very high pressure measurements. Pressure sensors used in biomedical applications need to be restricted in size and to be made biocompatible, whereas the pressure sensors used in industries needs to survive in harsh environmental conditions. These application requirements drive and impose tremendous conditions on sensor design to overcome tedious design and fabrication procedure before its reality. In case of an automobile, aircraft or biomedical system, a design engineer needs to select different range of pressure sensor to be incorporated into the system. Testing the suitability of a sensor requires knowledge on sensor performance. Usually, it consumes time and cost to finalize the sensor. There is a need of a ready reckoner to help the design engineers to select the sensors with optimal performance before freezing the final design. In order to hope up this, this thesis focuses on the design, analysis, and model verification by virtual prototyping and geometry optimization of a micro pressure sensor that can be fabricated using MEMS technology. A micro pressure sensor with diaphragm as the sensing element and three types of diaphragm geometry such as square, circular and doughnut type are considered and analyzed in this work. Three transduction methods that convert the applied pressure into suitable form of measurement namely capacitive, piezoresistive and resonant are considered in this work. Initially, the analytical design of the structures and the transduction techniques are carried out using Matlab as tool. Later, the models are virtually prototyped using a commercial FEM tool called COMSOL Multiphysics. The results of analytical design and virtual prototype models are compared and verified. Linearity and sensitivity analysis of the models are carried out and are used for optimization. The modeled structures are optimized using genetic algorithm to obtain the optimal sensor geometry and dimensions for its better performance and reduced size.

Item Type: Thesis (Phd. Thesis)
Subjects: Engineering > MIT Manipal > Instrumentation and Control
Depositing User: MIT Library
Date Deposited: 06 Nov 2014 11:22
Last Modified: 06 Nov 2014 11:22
URI: http://eprints.manipal.edu/id/eprint/140990

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