Enabling Adaptive and Enhanced Acoustic Sensing Using Nonlinear Dynamics

TL;DR

This paper introduces adaptive acoustic sensors utilizing nonlinear dynamics in mechanical oscillators to improve data relevance, dynamic range, and signal quality, facilitating more efficient real-time acoustic data acquisition.

Contribution

It presents a novel approach to adaptive sensing by integrating nonlinear dynamics into mechanical oscillators for enhanced acoustic signal processing.

Findings

Enhanced dynamic range and frequency resolution

Improved signal-to-noise ratio in acoustic sensing

Potential for acquiring only relevant information

Abstract

Transmission of real-time data is strongly increasing due to remote processing of sensor data, among other things. A route to meet this demand is adaptive sensing, in which sensors acquire only relevant information using pre-processing at sensor level. We present here adaptive acoustic sensors based on mechanical oscillators with integrated sensing and actuation. Their dynamics are shifted into a nonlinear regime using feedback or coupling. This enhances dynamic range, frequency resolution and signal-to-noise ratio. Combining tunable sensing properties with sound analysis could enable acquiring of only relevant information rather than extracting this from irrelevant data by post-processing.