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Research on Flow Field Perception Based on Artificial Lateral Line Sensor System.
Liu, Guijie; Wang, Mengmeng; Wang, Anyi; Wang, Shirui; Yang, Tingting; Malekian, Reza; Li, Zhixiong.
Afiliação
  • Liu G; Department of Mechanical and Electrical Engineering & Key Laboratory of Ocean Engineering of Shang Dong Province, Ocean University of China, Qingdao 266100, China. liuguijie@ouc.edu.cn.
  • Wang M; Department of Mechanical and Electrical Engineering & Key Laboratory of Ocean Engineering of Shang Dong Province, Ocean University of China, Qingdao 266100, China. wmm@stu.ouc.edu.cn.
  • Wang A; Department of Mechanical and Electrical Engineering & Key Laboratory of Ocean Engineering of Shang Dong Province, Ocean University of China, Qingdao 266100, China. wanganyi@stu.ouc.edu.cn.
  • Wang S; Department of Mechanical and Electrical Engineering & Key Laboratory of Ocean Engineering of Shang Dong Province, Ocean University of China, Qingdao 266100, China. wsr@stu.ouc.edu.cn.
  • Yang T; Department of Mechanical and Electrical Engineering & Key Laboratory of Ocean Engineering of Shang Dong Province, Ocean University of China, Qingdao 266100, China. yangtingting@stu.ouc.edu.cn.
  • Malekian R; Department of Electrical, Electronic & Computer Engineering, University of Pretoria, Pretoria 0002, South Africa. reza.malekian@ieee.org.
  • Li Z; School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, Wollongong 2522, NSW, Australia. zhixiong.li@ieee.org.
Sensors (Basel) ; 18(3)2018 Mar 11.
Article em En | MEDLINE | ID: mdl-29534499
ABSTRACT
In nature, the lateral line of fish is a peculiar and important organ for sensing the surrounding hydrodynamic environment, preying, escaping from predators and schooling. In this paper, by imitating the mechanism of fish lateral canal neuromasts, we developed an artificial lateral line system composed of micro-pressure sensors. Through hydrodynamic simulations, an optimized sensor structure was obtained and the pressure distribution models of the lateral surface were established in uniform flow and turbulent flow. Carrying out the corresponding underwater experiment, the validity of the numerical simulation method is verified by the comparison between the experimental data and the simulation results. In addition, a variety of effective research methods are proposed and validated for the flow velocity estimation and attitude perception in turbulent flow, respectively and the shape recognition of obstacles is realized by the neural network algorithm.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China