An electrostatic-capacitive Micro Electro-Mechanical System (MEMS) inclinometer based on a position-feedback mechanism and data analysis with Segmented Overlapping Allan VARiance (S-OAVAR) are presented in this paper. A closed-loop mechanism allows to keep the position of the movable proof mass of the MEMS sensor fixed while is acted upon by gravity, and to electrically tune the angle sensitivity and measurement range of the sensor independently from the working position. To investigate the evolution of noise contributions affecting the sensor over specific time frames of the day, a 15-hour data set of acquired measurements has been divided in one-hour segments each, and have been analysed with the OAVAR, thus leading to a S-OAVAR. Experimental results have shown that the angle sensitivity can be tuned from 9.41 mV/deg up to 33.1 mV/deg. The S-OAVAR analysis has highlighted the presence of distinctive noise contributions over time introduced by different environmental conditions such as mechanical vibrations induced by foot and vehicular traffics.
MEMS Inclinometer with Tunable-Sensitivity and Segmented Overlapping Allan Variance Analysis
Nastro A.;Ferrari M.;Ferrari V.
2020-01-01
Abstract
An electrostatic-capacitive Micro Electro-Mechanical System (MEMS) inclinometer based on a position-feedback mechanism and data analysis with Segmented Overlapping Allan VARiance (S-OAVAR) are presented in this paper. A closed-loop mechanism allows to keep the position of the movable proof mass of the MEMS sensor fixed while is acted upon by gravity, and to electrically tune the angle sensitivity and measurement range of the sensor independently from the working position. To investigate the evolution of noise contributions affecting the sensor over specific time frames of the day, a 15-hour data set of acquired measurements has been divided in one-hour segments each, and have been analysed with the OAVAR, thus leading to a S-OAVAR. Experimental results have shown that the angle sensitivity can be tuned from 9.41 mV/deg up to 33.1 mV/deg. The S-OAVAR analysis has highlighted the presence of distinctive noise contributions over time introduced by different environmental conditions such as mechanical vibrations induced by foot and vehicular traffics.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
