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Sensor placement optimization in the artificial lateral line using optimal weight analysis combining feature distance

Dong Xu1, Zhiyu Lv1, Haining Zeng1

  • 1School of Automation Science and Electrical Engineering, Beihang University, No. 37 Xueyuan Road, Beijing 100191, China.

ISA Transactions
|November 14, 2018
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Summary

An optimal weight analysis algorithm improves artificial lateral line sensor placement on robotic fish. This method reduces information loss and redundancy for better flow field perception.

Keywords:
Artificial lateral lineOptimal weight analysisRobotic fishSensor placement

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Area of Science:

  • Robotics
  • Fluid Dynamics
  • Sensor Systems

Background:

  • Artificial lateral lines mimic fish sensory systems for flow field perception.
  • Suboptimal sensor placement in artificial lateral lines causes information loss and redundancy.

Purpose of the Study:

  • To propose an optimal weight analysis algorithm for sensor placement in robotic fish artificial lateral lines.
  • To enhance flow field perception by minimizing information loss and redundancy.

Main Methods:

  • Signal features extracted from pressure data at candidate sensor locations.
  • Improved distance evaluation used to determine feature importance (weight).
  • Analysis of variance combined with feature weights to obtain sensor location contribution vectors.

Main Results:

  • An algorithm effectively determines optimal sensor placement and quantity for robotic fish.
  • Simulation and experimental results validate the algorithm's effectiveness.
  • Identified optimal number of sensors for improved performance.

Conclusions:

  • The proposed algorithm effectively addresses sensor placement challenges in artificial lateral lines.
  • Optimized sensor placement enhances the accuracy of flow field parameter perception.
  • Algorithm provides a robust method for designing multi-sensor systems.