TY - JOUR
T1 - A bionic seal whisker Karman vortex street sensor with wet-end electroless design
AU - Zhang, Jinying
AU - Shi, Yifan
AU - Li, Shihao
AU - Liu, Haoran
AU - Peng, Jianyu
AU - Gao, Zhongwei
AU - Wu, Xianmei
AU - Ai, Danni
AU - Yang, Jian
N1 - Publisher Copyright:
© 2026 Published by Elsevier B.V.
PY - 2026/10/1
Y1 - 2026/10/1
N2 - The Kármán vortex street represents a fundamental type of water flow vortex, encapsulating valuable intrinsic information—such as the distinctive features of marine organisms, including fish schools. Research has shown that seals use their vibrissae to detect Kármán vortex street signals generated by fish during predation, highlighting the significant potential of Kármán vortex street wake detection technology in applications like marine technology. This study introduces a novel bionic approach: a method for developing a Kármán vortex street sensor by integrating a bionic seal vibrissa structure with a fiber Bragg grating (FBG)-based vibration sensing configuration. This method aims to address the limitations of traditional electrical sensors, which are prone to electromagnetic interference (EMI) and are unsuitable for operation in humid or underwater environments. The detection capability of this sensor for Kármán vortex street wakes is also evaluated. Specifically, COMSOL Multiphysics software was used for modeling, simulation, and validation of the theoretical framework. The bionic sensing structure was fabricated using 3D printing technology, and experimental verification was carried out on large-scale fluid experimental platforms, such as high-speed water tunnels and wind tunnels. The sensor demonstrated high-accuracy detection across a wide range of fluid velocities, from 1.05 m/s to 16.8 m/s. The experimental results confirm that the proposed sensing structure achieves exceptional detection accuracy and versatility, overcoming the limitations of conventional electrical sensing methods and contributing significantly to the field of Kármán vortex street detection.
AB - The Kármán vortex street represents a fundamental type of water flow vortex, encapsulating valuable intrinsic information—such as the distinctive features of marine organisms, including fish schools. Research has shown that seals use their vibrissae to detect Kármán vortex street signals generated by fish during predation, highlighting the significant potential of Kármán vortex street wake detection technology in applications like marine technology. This study introduces a novel bionic approach: a method for developing a Kármán vortex street sensor by integrating a bionic seal vibrissa structure with a fiber Bragg grating (FBG)-based vibration sensing configuration. This method aims to address the limitations of traditional electrical sensors, which are prone to electromagnetic interference (EMI) and are unsuitable for operation in humid or underwater environments. The detection capability of this sensor for Kármán vortex street wakes is also evaluated. Specifically, COMSOL Multiphysics software was used for modeling, simulation, and validation of the theoretical framework. The bionic sensing structure was fabricated using 3D printing technology, and experimental verification was carried out on large-scale fluid experimental platforms, such as high-speed water tunnels and wind tunnels. The sensor demonstrated high-accuracy detection across a wide range of fluid velocities, from 1.05 m/s to 16.8 m/s. The experimental results confirm that the proposed sensing structure achieves exceptional detection accuracy and versatility, overcoming the limitations of conventional electrical sensing methods and contributing significantly to the field of Kármán vortex street detection.
KW - Bionics
KW - Fiber Bragg grating
KW - Kármán vortex street
KW - Sensor
UR - https://www.scopus.com/pages/publications/105039790309
U2 - 10.1016/j.sna.2026.117993
DO - 10.1016/j.sna.2026.117993
M3 - Article
AN - SCOPUS:105039790309
SN - 0924-4247
VL - 408
JO - Sensors and Actuators A: Physical
JF - Sensors and Actuators A: Physical
M1 - 117993
ER -