机电耦合对能量收集和减振同时应用的局部共振元结构的影响

IF 1 Q4 AUTOMATION & CONTROL SYSTEMS
M. Bukhari, Feng Qian, O. Barry, L. Zuo
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引用次数: 0

摘要

同时能量收集和振动衰减的研究是近年来许多声学超材料研究的焦点。这些研究报告了利用机电耦合收集电力的可能性;然而,机电谐振器对得到的带隙边界的影响还没有研究。本文研究了与机电谐振器耦合的超材料,通过分析和实验证明了机电耦合对波传播的影响。机电谐振器被分流到外部负载电阻以收集能量。我们推导了系统的解析色散曲线,并给出了不同负载电阻和机电耦合系数下的带结构。为了验证解析的色散关系,我们还对系统进行了数值模拟。并进行了实验验证。所获得的观察结果可以指导设计人员选择机电谐振器参数,以有效地从超材料中收集能量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effect of Electromechanical Coupling on Locally Resonant Metastructures for Simultaneous Energy Harvesting and Vibration Attenuation Applications
The study of simultaneous energy harvesting and vibration attenuation has recently been the focus in many acoustic meta-materials investigations. The studies have reported the possibility of harvesting electric power using electromechanical coupling; however, the effect of the electromechanical resonator on the obtained bandgap’s boundaries has not been explored yet. In this paper, we investigate metamaterial coupled to electromechanical resonators to demonstrate the effect of electromechanical coupling on the wave propagation analytically and experimentally. The electromechanical resonator is shunted to an external load resistor to harvest energy. We derive the analytical dispersion curve of the system and show the band structure for different load resistors and electromechanical coupling coefficients. To verify the analytical dispersion relations, we also simulate the system numerically. Furthermore, experiment is carried out to validate the analytical observations. The obtained observations can guide designers in selecting electromechanical resonator parameters for effective energy harvesting from meta-materials.
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来源期刊
Mechatronic Systems and Control
Mechatronic Systems and Control AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.40
自引率
66.70%
发文量
27
期刊介绍: This international journal publishes both theoretical and application-oriented papers on various aspects of mechatronic systems, modelling, design, conventional and intelligent control, and intelligent systems. Application areas of mechatronics may include robotics, transportation, energy systems, manufacturing, sensors, actuators, and automation. Techniques of artificial intelligence may include soft computing (fuzzy logic, neural networks, genetic algorithms/evolutionary computing, probabilistic methods, etc.). Techniques may cover frequency and time domains, linear and nonlinear systems, and deterministic and stochastic processes. Hybrid techniques of mechatronics that combine conventional and intelligent methods are also included. First published in 1972, this journal originated with an emphasis on conventional control systems and computer-based applications. Subsequently, with rapid advances in the field and in view of the widespread interest and application of soft computing in control systems, this latter aspect was integrated into the journal. Now the area of mechatronics is included as the main focus. A unique feature of the journal is its pioneering role in bridging the gap between conventional systems and intelligent systems, with an equal emphasis on theory and practical applications, including system modelling, design and instrumentation. It appears four times per year.
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