Enhanced Measurements in Fourier Analysis of MEMS Dynamics
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This thesis presents a method for dynamic characterization of MEMS structures and discuses parameters that affect its measurements and techniques to improve them. Current methods of non-contact, laser based vibration measurement require special and expensive instruments. The method used in this thesis on the other hand, relies on Fast Fourier Transform analysis of blurred images captured using conventional cameras. The Fourier series analysis and transformation are introduced. Basic concepts of blur image analysis and associated technical terms are described. Step by step data extraction process for Fourier analysis of blurred images and results such as amplitude, attenuation, signal to noise ratio and Bessel curve are explained. Macro and micro scale experiments are designed and used to determine the effect and significance of different parameters on signal-to-noise ratio of extracted results. For this purpose geometrical parameters of macro scale combs such as length, width and duty cycle are varied across a considerable range and tests results are examined. In addition to the experiments, MATLAB code is used to model environmental effects such as addition of noise or changes of brightness. In micro scale experiments, extra patterns are created using Focused Ion Beam and etching process. Test and comparison of modified micro structures with unpatterned structures show improvement in signal to noise ratio especially in environments with high level of noise.