Research on Flow Field Perception Based on Artificial Lateral Line Sensor System

Research on Flow Field Perception Based on Artificial Lateral Line Sensor System

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 compo...

Full description

Bibliographic Details
Main Authors: Guijie Liu, Mengmeng Wang, Anyi Wang, Shirui Wang, Tingting Yang, Reza Malekian, Zhixiong Li
Format: Article
Language:English
Published: MDPI AG 2018-03-01
Series:Sensors
Subjects:
artificial lateral line system
hydrodynamic simulation
flow field perception
velocity estimation
neural network
Online Access:http://www.mdpi.com/1424-8220/18/3/838
id doaj-2e95199801184256b83cd22b98999714
record_format Article
spelling doaj-2e95199801184256b83cd22b989997142020-11-24T22:07:15ZengMDPI AGSensors1424-82202018-03-0118383810.3390/s18030838s18030838Research on Flow Field Perception Based on Artificial Lateral Line Sensor SystemGuijie Liu0Mengmeng Wang1Anyi Wang2Shirui Wang3Tingting Yang4Reza Malekian5Zhixiong Li6Department of Mechanical and Electrical Engineering & Key Laboratory of Ocean Engineering of Shang Dong Province, Ocean University of China, Qingdao 266100, ChinaDepartment of Mechanical and Electrical Engineering & Key Laboratory of Ocean Engineering of Shang Dong Province, Ocean University of China, Qingdao 266100, ChinaDepartment of Mechanical and Electrical Engineering & Key Laboratory of Ocean Engineering of Shang Dong Province, Ocean University of China, Qingdao 266100, ChinaDepartment of Mechanical and Electrical Engineering & Key Laboratory of Ocean Engineering of Shang Dong Province, Ocean University of China, Qingdao 266100, ChinaDepartment of Mechanical and Electrical Engineering & Key Laboratory of Ocean Engineering of Shang Dong Province, Ocean University of China, Qingdao 266100, ChinaDepartment of Electrical, Electronic & Computer Engineering, University of Pretoria, Pretoria 0002, South AfricaSchool of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, Wollongong 2522, NSW, AustraliaIn 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.http://www.mdpi.com/1424-8220/18/3/838artificial lateral line systemhydrodynamic simulationflow field perceptionvelocity estimationneural network
collection DOAJ
language English
format Article
sources DOAJ
author Guijie Liu
Mengmeng Wang
Anyi Wang
Shirui Wang
Tingting Yang
Reza Malekian
Zhixiong Li
spellingShingle Guijie Liu
Mengmeng Wang
Anyi Wang
Shirui Wang
Tingting Yang
Reza Malekian
Zhixiong Li
Research on Flow Field Perception Based on Artificial Lateral Line Sensor System
Sensors
artificial lateral line system
hydrodynamic simulation
flow field perception
velocity estimation
neural network
author_facet Guijie Liu
Mengmeng Wang
Anyi Wang
Shirui Wang
Tingting Yang
Reza Malekian
Zhixiong Li
author_sort Guijie Liu
title Research on Flow Field Perception Based on Artificial Lateral Line Sensor System
title_short Research on Flow Field Perception Based on Artificial Lateral Line Sensor System
title_full Research on Flow Field Perception Based on Artificial Lateral Line Sensor System
title_fullStr Research on Flow Field Perception Based on Artificial Lateral Line Sensor System
title_full_unstemmed Research on Flow Field Perception Based on Artificial Lateral Line Sensor System
title_sort research on flow field perception based on artificial lateral line sensor system
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2018-03-01
description 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.
topic artificial lateral line system
hydrodynamic simulation
flow field perception
velocity estimation
neural network
url http://www.mdpi.com/1424-8220/18/3/838
work_keys_str_mv AT guijieliu researchonflowfieldperceptionbasedonartificiallaterallinesensorsystem
AT mengmengwang researchonflowfieldperceptionbasedonartificiallaterallinesensorsystem
AT anyiwang researchonflowfieldperceptionbasedonartificiallaterallinesensorsystem
AT shiruiwang researchonflowfieldperceptionbasedonartificiallaterallinesensorsystem
AT tingtingyang researchonflowfieldperceptionbasedonartificiallaterallinesensorsystem
AT rezamalekian researchonflowfieldperceptionbasedonartificiallaterallinesensorsystem
AT zhixiongli researchonflowfieldperceptionbasedonartificiallaterallinesensorsystem
_version_ 1725821290242113536

Similar Items