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Title: A Vector Sensor-Based Acoustic Characterization System for Marine Renewable Energy

Abstract

NoiseSpotter is a passive acoustic monitoring system that characterizes, classifies, and geo-locates anthropogenic and natural sounds in near real time. It was developed with the primary goal of supporting the evaluation of potential acoustic effects of offshore renewable energy projects. The system consists of a compact array of three acoustic vector sensors, which measures acoustic pressure and the three-dimensional particle velocity vector associated with the propagation of an acoustic wave, thereby inherently providing bearing information to an underwater source of sound. By utilizing an array of three vector sensors, the application of beamforming techniques can provide sound source localization, allowing for characterization of the acoustic signature of specific underwater acoustic sources. Here, performance characteristics of the system are presented, using data from controlled acoustic transmissions in a quiet environment and ambient noise measurements in an energetic tidal channel in the presence of non-acoustic flow noise. Data quality is demonstrated by the ability to reduce non-acoustic flow noise contamination, while system utility is shown by the ability to characterize and localize sources of sound in the underwater environment.

Authors:
; ORCiD logo; ;
Publication Date:
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1603825
Grant/Contract Number:  
[EE0007822]
Resource Type:
Published Article
Journal Name:
Journal of Marine Science and Engineering
Additional Journal Information:
[Journal Name: Journal of Marine Science and Engineering Journal Volume: 8 Journal Issue: 3]; Journal ID: ISSN 2077-1312
Publisher:
MDPI AG
Country of Publication:
Switzerland
Language:
English

Citation Formats

Raghukumar, Kaustubha, Chang, Grace, Spada, Frank, and Jones, Craig. A Vector Sensor-Based Acoustic Characterization System for Marine Renewable Energy. Switzerland: N. p., 2020. Web. doi:10.3390/jmse8030187.
Raghukumar, Kaustubha, Chang, Grace, Spada, Frank, & Jones, Craig. A Vector Sensor-Based Acoustic Characterization System for Marine Renewable Energy. Switzerland. doi:10.3390/jmse8030187.
Raghukumar, Kaustubha, Chang, Grace, Spada, Frank, and Jones, Craig. Tue . "A Vector Sensor-Based Acoustic Characterization System for Marine Renewable Energy". Switzerland. doi:10.3390/jmse8030187.
@article{osti_1603825,
title = {A Vector Sensor-Based Acoustic Characterization System for Marine Renewable Energy},
author = {Raghukumar, Kaustubha and Chang, Grace and Spada, Frank and Jones, Craig},
abstractNote = {NoiseSpotter is a passive acoustic monitoring system that characterizes, classifies, and geo-locates anthropogenic and natural sounds in near real time. It was developed with the primary goal of supporting the evaluation of potential acoustic effects of offshore renewable energy projects. The system consists of a compact array of three acoustic vector sensors, which measures acoustic pressure and the three-dimensional particle velocity vector associated with the propagation of an acoustic wave, thereby inherently providing bearing information to an underwater source of sound. By utilizing an array of three vector sensors, the application of beamforming techniques can provide sound source localization, allowing for characterization of the acoustic signature of specific underwater acoustic sources. Here, performance characteristics of the system are presented, using data from controlled acoustic transmissions in a quiet environment and ambient noise measurements in an energetic tidal channel in the presence of non-acoustic flow noise. Data quality is demonstrated by the ability to reduce non-acoustic flow noise contamination, while system utility is shown by the ability to characterize and localize sources of sound in the underwater environment.},
doi = {10.3390/jmse8030187},
journal = {Journal of Marine Science and Engineering},
number = [3],
volume = [8],
place = {Switzerland},
year = {2020},
month = {3}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.3390/jmse8030187

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