利用光纤法布里-佩罗干涉仪对 MEMS 生物模拟麦克风的机械灵敏度进行基于快速解调白光干涉测量和理论验证

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Dipeng Ren;Xiaonan Yang;Zhi-Mei Qi
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引用次数: 0

摘要

为了实现声源定位(SSL)的微型化,人们广泛研究了受苍蝇 Ormia ochracea 的耦合耳启发的 MEMS 麦克风。然而,目前所有仿生传声器的声源定位都依赖于从仿生振膜的定向振动转换而来的电信号。因此,只有生物仿生传声器在声压激励下的电性能(即电灵敏度 mV/Pa)得到了表征,而机械性能(即机械灵敏度 nm/Pa)却没有得到表征。表征机械灵敏度不仅能直接表示仿生麦克风的声学响应大小,还能直接验证相应的理论模型。因此,在本文中,我们设计并制造了带有光纤法布里-佩罗干涉仪(FPI)的 MEMS 拟生物传声器,并在此基础上首次成功地利用快速解调白光干涉仪(WLI)测量了拟生物传声器的机械灵敏度。此外,我们还首次推导出了具有精确表达式的改进理论模型,以更好地描述仿生麦克风的声学响应,而且理论和测量结果在机械灵敏度方面可以相互印证。因此,本研究验证了直接测量仿生麦克风声学响应的可行方案,并构建了更有效、更详细的理论模型来描述该声学响应。本文的研究结果不仅能为未来设计解调系统的动态范围和线性解调间隔提供数值参考,还能促进对仿生麦克风工作机理的深入理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast Demodulated White-Light Interferometry-Based Measurement and Theoretical Verification of Mechanical Sensitivity of MEMS Biomimetic Microphone With Fiber-Optic Fabry-Pérot Interferometer
MEMS microphones inspired by the coupled ears of the fly Ormia ochracea have been extensively studied to achieve miniaturization of sound source localization (SSL). However, the SSL of all current biomimetic microphones relies on the electrical signals converted from the directional vibration of the biomimetic diaphragms. Consequently, only the electrical performance of the biomimetic microphones under sound pressure excitation (i.e., electrical sensitivity mV/Pa) has been characterized, whereas the mechanical performance (i.e., mechanical sensitivity nm/Pa) has not. Characterizing the mechanical sensitivity can not only directly represent the acoustic response magnitude of the biomimetic microphones but also directly verify the corresponding theoretical models. Therefore, in this article, we designed and fabricated an MEMS biomimetic microphone with a fiber-optic Fabry-Pérot interferometer (FPI), based on which we successfully measured the mechanical sensitivity of the biomimetic microphone by the fast demodulated white-light interferometry (WLI) for the first time. In addition, an improved theoretical model with exact expressions was first derived to better describe the acoustic response of the biomimetic microphone, and the theoretical and measurement results can be corroborated by each other in terms of mechanical sensitivity. Therefore, this study verifies a feasible solution to directly measure the acoustic response of the biomimetic microphone and constructs a more effective and detailed theoretical model to describe this acoustic response. The results in this article can not only provide a numerical reference for designing future demodulation systems regarding the dynamic range and the linear demodulation interval but also promote a deeper understanding of the working mechanism of the biomimetic microphones.
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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