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

• Published in: Sensors (Basel, Switzerland) Vol. 18; no. 3; p. 838
• Main Authors: Liu, Guijie, Wang, Mengmeng, Wang, Anyi, Wang, Shirui, Yang, Tingting, Malekian, Reza, Li, Zhixiong
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 11.03.2018; MDPI
• Subjects: artificial lateral line system; Computational fluid dynamics; Computer simulation; Fish; flow field perception; Flow velocity; hydrodynamic simulation; neural network; Neural networks; Perception; Predators; Pressure distribution; Pressure sensors; Stress concentration; Turbulence; Turbulent flow; Uniform flow; velocity estimation; flow field perception; hydrodynamic simulation; neural network; velocity estimation; artificial lateral line system
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s18030838

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.