JOURNAL ARTICLE
The barometric-pressure sensor as a comparison-calibration reference for acoustics from 0.01 to 10 hertz.
Published In: Journal of the Acoustical Society of America, 2025, v. 157, n. 5. P. 3538 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Gabrielson, Thomas B.; Talmadge, Carrick L.; Smith, Chad M. 3 of 3
Abstract
This article focuses on developing a method to use a barometric-pressure sensor with a well-characterized complex frequency response as a reference for comparison calibration of infrasound sensors in the challenging frequency range from near-zero (DC) to tens of hertz. Specifically, it demonstrates that the Setra 278 barometric-pressure sensor, which has a simple second-order low-pass frequency response model defined by two parameters—the DC response (S0) traceable to the National Institute of Standards and Technology (NIST) and a characteristic frequency (f0)—can serve as a low-uncertainty reference sensor for infrasonic calibration. The characteristic frequency f0 is determined by fitting the sensor's phase response against that of a calibrated infrasound microphone (e.g., Brüel & Kjær BK4193), and its uncertainty is estimated via Monte Carlo simulations based on the microphone's calibration uncertainties. The approach yields combined uncertainties in magnitude and phase for the Setra 278 that are lower than those of the infrasound microphone used for calibration, enabling laboratories without primary calibration capabilities to perform traceable secondary calibrations with uncertainties well below one percent in the 0.01 to 10 Hz frequency range.
Additional Information
- Source:Journal of the Acoustical Society of America. 2025/05, Vol. 157, Issue 5, p3538
- Document Type:Article
- Subject Area:Earth and Atmospheric Sciences
- Publication Date:2025
- ISSN:0001-4966
- DOI:10.1121/10.0036659
- Accession Number:185593253
- Copyright Statement:Copyright of Journal of the Acoustical Society of America is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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