Bioinspired Tapered-Spring Turbulence Sensor for Underwater Flow Detection

TL;DR

This work tackles robust underwater flow sensing in challenging environments by introducing a bio-inspired tapered-spring whisker that passively encodes hydrodynamic disturbances into distributed mechanical states. By integrating three spatially distributed MEMS IMUs and applying a lightweight PRC-inspired readout (logistic regression), the system achieves real-time wake-state identification with low power consumption. Through towing-tank experiments and CFD, the authors demonstrate intrinsic frequency–spatial decoupling, accurate vortex shedding frequency estimation, and entropy-based tracking of wake transitions, with ms-scale inference and sub-4–10% frequency error. The approach offers a scalable, energy-efficient sensing solution for wake tracking and turbulence-aware navigation in autonomous underwater vehicles, with potential extensions to multi-whisker arrays and adaptive stiffness for distributed flow-field mapping.

Abstract

This paper presents a bio-inspired underwater whisker sensor for robust hydrodynamic disturbance detection and efficient signal analysis based on Physical Reservoir Computing (PRC). The design uses a tapered nylon spring with embedded accelerometers to achieve spatially distributed vibration sensing and frequency separation along the whisker. Towing-tank experiments and computational fluid dynamics simulations confirmed that the whisker effectively distinguishes vortex regimes across different fin angles and maintains Strouhal scaling with flow velocity, where higher speeds increase vibration intensity without affecting the dominant frequencies. Frequency-domain analysis, Shannon entropy, and machine learning further validated the sensing performance: vortex shedding frequencies were identified with less than 10\% error, entropy captured the transition from coherent vortex streets to turbulence, and logistic regression achieved 86.0\% classification accuracy with millisecond-level inference. These results demonstrate that structurally encoded whisker sensing provides a scalable and real-time solution for underwater perception, wake tracking, and turbulence-aware navigation in autonomous marine robots.

Figures (10)

• Figure 1: Tapered spring-based whisker sensor for fluid interaction sensing. The system includes a 3D-printed nylon PA12 conical spring with embedded accelerometers, enabling spatially distributed vibration sensing for physical reservoir computing.
• Figure 2: Harmonic response modes of the encapsulated whisker structure at various frequencies. Three distinct modal concentrations emerge along the length, enabling spatial encoding under fluid-induced oscillation.
• Figure 3: Custom-designed compact PCB integrating the ICM-42670P IMU sensor. The overall footprint is approximately 12.5mm×8mm, allowing for seamless embedding into the the whisker structure.
• Figure 4: (a) Schematic of the test platform and signal processing workflow. The setup includes a water tank with a V-shaped guide rail, a motion control mechanism for precisely adjusting the fin and bioinspired whisker, and a signal acquisition and processing system. The submerged whisker structure generates vibration signals under different flow conditions, which are collected by a microcontroller and transmitted to a PC for frequency-domain analysis.
• Figure 5: Normalized frequency response spectra of the three IMU sensors placed along the tapered whisker structure. The results demonstrate distinct frequency sensitivities depending on the sensor's position, with the bottom sensor responding predominantly to mid and high frequencies, and the top sensor exhibiting stronger responses in the low-frequency range.