Current development of bionic flexible sensors applied to marine flow field detection

Xia, Qinglin; Song, Nan; Liu, Chen; Zhai, Ruixue; Ai, Chao; Sun, Xu; Zhang, Sheng

doi:10.1016/j.sna.2023.114158

Cited by 7 publications

(1 citation statement)

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“…Up to now, inspired by the superficial neuromast of fish, numerous articles have been published on the artificial lateral line system, and scholars in the field have also made a comprehensive summary of the artificial lateral line system, such as literature [13][14][15][16]. The progress of the artificial lateral line system is remarkable, and the output of the literature is frequent.…”

Section: Introductionmentioning

confidence: 99%

Research on the application of artificial lateral line system for different sensing effects of fish

Zhao,

Lei

2023

Ninth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023)

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The lateral line system is an essential sensing organ formed by the long-term optimization of fish for hundreds of millions of years. It has excellent sensing ability in complex underwater environments. Fish can use the lateral line system to detect objects' orientation and analyze the surrounding fluid's dynamic properties and other adequate information. The biological behaviour of fish is closely related to the lateral line system, manifested in the avoidance of natural enemies, population communication, food intake and so on. Firstly, this article elaborates on the physiological characteristics of the lateral line system in fish and distinguishes the functions and roles of different nerve neuromasts. Secondly, the superficial flow sensors based on other sensing principles in recent years are reviewed, and the application of piezoelectric and piezoresistive sensors in the artificial lateral line system is emphasized. In the end, the paper makes a comprehensive summary and outlook, summarizes the current challenges, and points out the necessary research directions for the future.

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Section: Introductionmentioning

confidence: 99%