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基于鱼类侧线系统的流场感知。

Flow field perception based on the fish lateral line system.

机构信息

School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, People's Republic of China.

出版信息

Bioinspir Biomim. 2019 May 3;14(4):041001. doi: 10.1088/1748-3190/ab1a8d.

Abstract

Fish are able to perceive the surrounding weak flow and pressure variations with their mechanosensory lateral line system, which consists of a superficial lateral line for flow velocity detection and a canal lateral line for flow pressure gradient perception. Achieving a better understanding of the flow field perception algorithms of the lateral line can contribute not only to the design of highly sensitive flow sensors, but also to the development of underwater smart skin with good hydrodynamic imaging properties. In this review, we discuss highly sensitive flow-sensing mechanisms for superficial and canal neuromasts and flow field perception algorithms. Artificial lateral line systems with different transduction mechanisms are then described with special emphasis on the recent innovations in the field of polymer-based artificial flow sensors. Finally, we discuss our perspective of the technological challenges faced while improving flow sensitivity, durability, and sensing fusion schemes.

摘要

鱼类能够通过其机械感觉侧线系统感知周围的微弱流速和压力变化,该系统包括用于检测流速的表面侧线和用于感知流速压力梯度的管侧线。更好地理解侧线的流场感知算法不仅有助于设计高灵敏度的流量传感器,也有助于开发具有良好水动力成像性能的水下智能皮肤。在这篇综述中,我们讨论了用于表面和管神经丘的高灵敏度流量感应机制以及流场感知算法。然后,我们描述了具有不同转换机制的人工侧线系统,特别强调了聚合物基人工流量传感器领域的最新创新。最后,我们讨论了在提高流量灵敏度、耐用性和传感融合方案方面面临的技术挑战的看法。

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