2017•The Journal of the Acoustical Society of AmericaRequires access

Characterization of the vibration response of miniature microphones by subtraction

Jonathan D. Walsh, Quang T. Su, Daniel Max Warren

Open publisher page 1 citations

Abstract

Presented is a test methodology for characterizing the vibration sensitivity of miniature microphones for hearing aids. A common method for obtaining the vibration sensitivity of a system is to use an electrodynamic shaker to deliver a calibrated vibration input and measure the corresponding output. When the system under test is a microphone, it is difficult to obtain the vibration response since the measured output will also be due to coherent sound created by the vibration delivery system. The method models the microphone as a system with two inputs, vibration and sound, with one electronic output. Using frequency-domain signal processing, this method extracts the vibration response from a shaker-driven signal by subtracting a synthesized acoustic response signal. When compared to vibration measurements under vacuum, the vibration responses from the two methods generally agree. The vibration response estimates produced using this algorithm are more accurate than vacuum chamber data due to the loading and stiffening effects caused by the presence of air, as would occur under standard operating conditions. This test method allows the rapid acquisition of microphone vibration responses by eliminating the need for a vacuum chamber, or carefully designed acoustic baffling.

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What this paper is about

Presented is a test methodology for characterizing the vibration sensitivity of miniature microphones for hearing aids. A common method for obtaining the vibration sensitivity of a system is to use an electrodynamic shaker to deliver a calibrated vibration input and measure the corresponding output. When the system under test is a microphone, it is difficult to obtain the vibration response since the measured output will also be due to coherent sound created by the vibration delivery system. The method models the microphone as a system with two inputs, vibration and sound, with one electronic output. Using frequency-domain signal processing, this method extracts the vibration response from a shaker-driven signal by subtracting a synthesized acoustic response signal. When compared to vibration measurements under vacuum, the vibration responses from the two methods generally agree. The vibration response estimates produced using this algorithm are more accurate than vacuum chamber data due to the loading and stiffening effects caused by the presence of air, as would occur under standard operating conditions. This test method allows the rapid acquisition of microphone vibration responses by eliminating the need for a vacuum chamber, or carefully designed acoustic baffling.

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Available abstract

Presented is a test methodology for characterizing the vibration sensitivity of miniature microphones for hearing aids. A common method for obtaining the vibration sensitivity of a system is to use an electrodynamic shaker to deliver a calibrated vibration input and measure the corresponding output. When the system under test is a microphone, it is difficult to obtain the vibration response since the measured output will also be due to coherent sound created by the vibration delivery system. The method models the microphone as a system with two inputs, vibration and sound, with one electronic output. Using frequency-domain signal processing, this method extracts the vibration response from a shaker-driven signal by subtracting a synthesized acoustic response signal. When compared to vibration measurements under vacuum, the vibration responses from the two methods generally agree. The vibration response estimates produced using this algorithm are more accurate than vacuum chamber data due to the loading and stiffening effects caused by the presence of air, as would occur under standard operating conditions. This test method allows the rapid acquisition of microphone vibration responses by eliminating the need for a vacuum chamber, or carefully designed acoustic baffling.

Key concepts: Acoustics, Vibration, Shaker, Microphone, Sensitivity (control systems), SIGNAL (programming language), Frequency response, Computer science

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