A comparison among three different image analysis methods for the displacement measurement in a novel MEMS device

The functional characterization of MEMS devices is of great importance today, since it has the purpose both of verifying the behavior of these devices and of improving their future design. In this regard, the main topic of this study is the functional characterization of a microgripper prototype, a MEMS suitable in biomedical applications: to this aim, the measurement of the angular displacement of its comb-drive (capacitive electrostatic actuator that allows its movement) is provided by means of two novel automatic procedures, based on an image analysis software, the SURF-based (Speeded Up Robust Features) and the FFT-based (Fast Fourier Transform) method respectively. A preliminary comparison has been made, also with a previous semiautomatic method, to evaluate which of them is the best suitable for the functional characterization of the microgripper, highlighting their main advantages and limitations. The results obtained from the SURF-based method are promising; the curve obtained from the data showed a quadratic trend in agreement with both the analytical model and with the results obtained through the semiautomatic method. Moreover, the measurement obtained by the SURF-based method are affected by less than 0.2° uncertainty, that is less than one half of the measurement uncertainty due to the FFT-based algorithm.