Literature DB >> 31661679

Amplitude information-frequency characteristics for multi-frequency excitation of underwater active electrolocation systems.

Qingxuan Ren1, Jiegang Peng, Hongjin Chen.   

Abstract

Underwater active electrolocation technology is a new kind of technology for underwater detection and environmental perception, whose discovery was inspired by the active electrolocation systems of weakly electric fish. The amplitude information-frequency characteristics (AIFC) obtained by an underwater active electrolocation system (UAES) can effectively assess information about probed objects, such as their material composition, shape, and conductivity. Traditionally, single-frequency excitation has been employed in a UAES, which can make object detection inefficient and time-consuming. We employed multi-frequency signals for excitation in a UAES, to improve the efficiency of detection. We used three kinds of multi-frequency excitation signals-square wave, single pulse, and biphasic pulse, to detect objects under water. To improve the accuracy of measurements, we developed an AIFC recognition algorithm. The experimental results showed that the multi-frequency excitation detection method is effective and feasible. We demonstrated that the electrodes are strongly coupled to the UAES and can result in non-negligible errors that have often been previously ignored. In addition, graphite electrodes performed much better than titanium electrodes for multi-frequency signal detection, and bio-inspired multi-frequency pulse excitation signals gave more accurate results than the square-wave signal.

Entities:  

Year:  2019        PMID: 31661679     DOI: 10.1088/1748-3190/ab526b

Source DB:  PubMed          Journal:  Bioinspir Biomim        ISSN: 1748-3182            Impact factor:   2.956


  1 in total

1.  Research on the Recognition Performance of Bionic Sensors Based on Active Electrolocation for Different Materials.

Authors:  Wenhao Du; Yu'e Yang; Luning Liu
Journal:  Sensors (Basel)       Date:  2020-08-17       Impact factor: 3.576

  1 in total

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