Please use this identifier to cite or link to this item: https://doi.org/10.48441/4427.763
Publisher DOI: 10.3390/s23052774
Title: Near-ultrasonic transfer function and SNR of differential MEMS microphones suitable for photoacoustics
Language: English
Authors: Falkhofen, Judith 
Wolff, Marcus  
Editor: Lázaro, Antonio 
Keywords: deconvolution; MEMS microphones; photoacoustic spectroscopy; sensitivity; SNR; ultrasound
Issue Date: 3-Mar-2023
Publisher: MDPI
Journal or Series Name: Sensors 
Volume: 23
Issue: 5
Abstract: 
Can ordinary Micro-Electro-Mechanical-Systems (MEMS) microphones be used for near-ultrasonic applications? Manufacturers often provide little information about the signal-to-noise ratio (SNR) in the ultrasound (US) range and, if they do, the data are often determined in a manufacturer-specific manner and are generally not comparable. Here, four different air-based microphones from three different manufacturers are compared with respect to their transfer functions and noise floor. The deconvolution of an exponential sweep and a traditional calculation of the SNR are used. The equipment and methods used are specified, which makes it easy to repeat or expand the investigation. The SNR of MEMS microphones in the near US range is mainly affected by resonance effects. These can be matched for applications with low-level signals and background noise such that the highest possible SNR can be achieved. Two MEMS microphones from Knowles performed best for the frequency range from 20 to 70 kHz; above 70 kHz, an Infineon model delivered the best performance.
URI: http://hdl.handle.net/20.500.12738/13691
DOI: 10.48441/4427.763
ISSN: 1424-8220
Review status: This version was peer reviewed (peer review)
Institute: Department Maschinenbau und Produktion 
Fakultät Technik und Informatik 
Heinrich-Blasius-Institut für Physikalische Technologien 
Type: Article
Additional note: Falkhofen, J.; Wolff, M. Near-Ultrasonic Transfer Function and SNR of Differential MEMS Microphones Suitable for Photoacoustics. Sensors 2023, 23, 2774, https://doi.org/10.3390/s23052774. The APC was funded by Hamburg University of Applied Sciences.
Funded by: Hochschule für Angewandte Wissenschaften Hamburg 
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