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Adaptive piezoelectric metamaterial beam: autonomous attenuation zone adjustment in complex vibration environments

Auteur(s):
ORCID
ORCID



Médium: article de revue
Langue(s): anglais
Publié dans: Smart Materials and Structures, , n. 10, v. 32
Page(s): 105023
DOI: 10.1088/1361-665x/acf62f
Abstrait:

Programmable metamaterials for broadband vibration control draw growing interest due to their abilities to tailor dynamic responses. However, the deterministic dynamic behavior of any traditional metamaterial is a challenge to cope with the complex and variable vibration conditions in real environments. This work proposes an adaptive piezoelectric metamaterial beam (piezo-meta-beam) that consists of bimorph piezoelectric arrays. The shunt circuits are designed with self-tuning abilities by integrating microcontroller-driven digital potentiometers into synthetic inductive circuits. Two typical scenarios are considered, i.e., harmonic and white noise excitations with different spectra. Different self-tuning strategies based on bandgap prediction are contrapuntally developed. However, a flaw in the analytical bandgap expression widely appearing in the literature is noted through a verification study. A modified bandgap expression based on the 3D finite element model is proposed for correction. This modified bandgap expression is adopted in formulating the control strategy of the microcontroller. A series of experiments are conducted to investigate the adaptive behavior of the piezo-meta-beam. In the harmonic sweep excitation test, the adaptive piezo-meta-beam shows an ultra-broad attenuation zone (220–720 Hz), while the traditional counterpart only has a bandgap width of less than 20 Hz. In the case of noise excitation, autonomous adjustment of the center frequency and attenuation zone is achieved for noises over different spectra. In general, this work presents a methodology for designing intelligent metamaterials that can adapt to environmental vibrations with vast potential for real applications.

Copyright: © 2023 Yupei Jian, Guobiao Hu, Lihua Tang, Yincheng Shen, Yulin Zhan, Kean Aw
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10740126
  • Publié(e) le:
    12.09.2023
  • Modifié(e) le:
    07.02.2024
 
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