Uncovering signals from measurement noise by electro mechanical amplitude modulation

Abstract

We present an electromechanical parametric scheme to improve the low-frequency signal-to-noise ratio of energy buffering type transducers. The method is based on periodic modulation of the stiffness in the sensory system which produces upconverted replicas of the signals of interest at frequencies where measurement is less troubled by noise or other detrimental effects. We demonstrate this principle by means of capacitive biomimetic hair flow sensors, where we modulate the rotational spring stiffness by periodic electrostatic spring softening, such that a replica of the original signal is formed around the modulation frequency. Using this replica we gain up to a 25-fold improvement of the low-frequency signal-to-noise ratio and sensing threshold. For transient measurements we demonstrate that tiny signals, which are below the noise-levels in the base-band, are revealed well when upconverted to higher frequencies.