Bioinspired Tapered-Spring Turbulence Sensor for Underwater Flow Detection
Fuente:
arXiv
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911199321391104 |
|---|---|
| author | Jin, Xiao Yu, Zhenhua Nanayakkara, Thrishantha |
| author_facet | Jin, Xiao Yu, Zhenhua Nanayakkara, Thrishantha |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_07348 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Bioinspired Tapered-Spring Turbulence Sensor for Underwater Flow Detection Jin, Xiao Yu, Zhenhua Nanayakkara, Thrishantha Instrumentation and Detectors Robotics Fluid Dynamics 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. |
| title | Bioinspired Tapered-Spring Turbulence Sensor for Underwater Flow Detection |
| topic | Instrumentation and Detectors Robotics Fluid Dynamics |
| url | https://arxiv.org/abs/2510.07348 |