Capacitive sensors are low-cost and robust devices that can be easily scaled to very small sizes, thus making them suitable for implementation as a micro electro-mechanical system (MEMS). Differential arrangements of the sensors are also available, providing improved rejection of common mode interference. Due to their nature, an AC (sinusoidal) excitation signal is usually adopted. Various types of front-end circuits have been proposed in the past, exploiting different techniques such as conversion of capacitance to current or frequency or analog-to-digital conversion and adopting different approaches, such as full analog or full digital architectures. This paper proposes a digital and microcontroller-based system for AC-excited differential sensors aiming at minimizing cost and power needs, in sight of future large volume applications as for Internet of Things (IoT) paradigm. A proof of concept implementation has been realized and experimentally validated, obtaining a relative error in the measurand estimation on the order of 1%, when the parasitic effects can be neglected.
Simple and power efficient interface for AC-excited differential sensors
Flammini A.;Barile G.;Ferri G.;Stornelli V.
2020-01-01
Abstract
Capacitive sensors are low-cost and robust devices that can be easily scaled to very small sizes, thus making them suitable for implementation as a micro electro-mechanical system (MEMS). Differential arrangements of the sensors are also available, providing improved rejection of common mode interference. Due to their nature, an AC (sinusoidal) excitation signal is usually adopted. Various types of front-end circuits have been proposed in the past, exploiting different techniques such as conversion of capacitance to current or frequency or analog-to-digital conversion and adopting different approaches, such as full analog or full digital architectures. This paper proposes a digital and microcontroller-based system for AC-excited differential sensors aiming at minimizing cost and power needs, in sight of future large volume applications as for Internet of Things (IoT) paradigm. A proof of concept implementation has been realized and experimentally validated, obtaining a relative error in the measurand estimation on the order of 1%, when the parasitic effects can be neglected.File | Dimensione | Formato | |
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