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Mechanism of a Hair Cell Bioinspired Sensor with Ultrasensitivity to Weak and Low Frequency Vibration Signals
Author(s) -
L. J. Liu,
Ying Lei
Publication year - 2013
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2013/278151
Subject(s) - computer science , vibration , mechanism (biology) , sensitivity (control systems) , acoustics , signal (programming language) , gating , transduction (biophysics) , biomimetics , hair cell , acceleration , low frequency , biological system , physics , inner ear , electronic engineering , biophysics , telecommunications , artificial intelligence , engineering , biology , neuroscience , quantum mechanics , classical mechanics , programming language
Although significant progresses have been made in sensor technology, it is still a challenging task to develop ultrasensitive sensors to monitor very weak and low frequency vibration signal for early warning of natural disasters and efficient structural health monitoring of infrastructures. It has been reported from previous experiments that some fishes have acute sensitivities to extremely low frequency linear acceleration due to the otolith organs of the inner ear. In this paper, based on the experimental results and qualitative mechanism of the infrasound sensitivity of some fishes conducted by other researchers, a bioinspired gating spring model with negative stiffness is established to simulate the mechanical-electricity transduction of the hair cell in fish ear. Then, numerical analyses of the mechanical model subject to static and dynamic loading are conducted, respectively. It is shown that the gating model has adaptive amplification capability to weak and low frequency excitation compared with the corresponding linear model. This mechanism can be used for the design of bioinspired ultrasensitive sensors for monitoring weak and low frequency vibration signal. © 2013 L. J. Liu and Y. Lei.

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