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1

Chambers, Derrick, Peiyao Li, Harpreet Sethi, and Jeffery Shragge. "Monitoring industrial acoustics with distributed acoustic sensing." Journal of the Acoustical Society of America 151, no. 4 (2022): A58. http://dx.doi.org/10.1121/10.0010648.

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True-phase distributed acoustic sensing (DAS), a technique which uses low-power laser pulses to monitor along-fiber strain in optical cable, has proven useful in many geophysical research areas, including down-hole monitoring in oil/gas extraction, near-surface characterization, detecting and locating regional and global earthquakes, urban monitoring. Most of the geophysical applications to date, however, have focused on recording elastic waves propagating through solid media. In this work, we explore the response of DAS for recording acoustic propagation in air, as a function of fiber type an
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Shang, Ying, Maocheng Sun, Chen Wang, et al. "Research Progress in Distributed Acoustic Sensing Techniques." Sensors 22, no. 16 (2022): 6060. http://dx.doi.org/10.3390/s22166060.

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Distributed acoustic sensing techniques based on Rayleigh scattering have been widely used in many applications due to their unique advantages, such as long-distance detection, high spatial resolution, and wide sensing bandwidth. In this paper, we provide a review of the recent advancements in distributed acoustic sensing techniques. The research progress and operation principles are systematically reviewed. The pivotal technologies and solutions applied to distributed acoustic sensing are introduced in terms of polarization fading, coherent fading, spatial resolution, frequency response, sign
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Abadi, Shima, William S. Wilcock, and Brad P. Lipovsky. "Detecting hydro-acoustic signals using Distributed Acoustics Sensing technology." Journal of the Acoustical Society of America 152, no. 4 (2022): A201. http://dx.doi.org/10.1121/10.0016027.

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Distributed Acoustic Sensing (DAS) is a relatively new technology that transforms fiber optic cables, typically used for telecommunications, into dense sensor arrays, capable of meter-scale recordings up to ∼100 km. The interest in these technologies for ocean exploration and monitoring has risen in recent years. These systems enable continuous and highly sensitive measurements of both temporal and spatial acoustic data. In this presentation, we use data recorded during a 4-day DAS experiment on the twin cables of the Ocean Observatories Initiative (OOI) Regional Cabled Array (RCA) extending o
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Shen, Zhichao, Wenbo Wu, and Ying-Tsong Lin. "High-resolution observations of shallow-water acoustic propagation with distributed acoustic sensing." Journal of the Acoustical Society of America 156, no. 4 (2024): 2237–49. http://dx.doi.org/10.1121/10.0030400.

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Distributed acoustic sensing (DAS), converting fiber-optic cables into dense acoustic sensors, is a promising technology that offers a cost-effective and scalable solution for long-term, high-resolution studies in ocean acoustics. In this paper, the telecommunication cable of Martha's Vineyard Coastal Observatory (MVCO) is used to explore the feasibility of cable localization and shallow-water sound propagation with a mobile acoustic source. The MVCO DAS array records coherent, high-quality acoustic signals in the frequency band of 105–160 Hz, and a two-step inversion method is used to improve
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Ellmauthaler, Andreas, Brian C. Seabrook, Glenn A. Wilson, et al. "Distributed acoustic sensing of subsea wells." Leading Edge 39, no. 11 (2020): 801–7. http://dx.doi.org/10.1190/tle39110801.1.

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Topside distributed acoustic sensing (DAS) of subsea wells requires advanced optical engineering solutions to compensate for reduced acoustic bandwidth, optical losses, and back reflections that are accumulated through umbilicals, multiple wet- and dry-mate optical connectors, splices, optical feedthrough systems, and downhole fibers. To address these issues, we introduce a novel DAS solution based on subsea fiber topology consisting of two transmission fibers from topside and an optical circulator deployed in the optical flying lead at the subsea tree. This solution limits the sensing fiber p
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Schmidt, Henrik. "Distributed acoustic sensing in shallow water." Journal of the Acoustical Society of America 120, no. 5 (2006): 3297. http://dx.doi.org/10.1121/1.4778019.

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Rosalie, Cedric, Nik Rajic, Patrick Norman, and Claire Davis. "Acoustic Source Localisation Using Distributed Sensing." Procedia Engineering 188 (2017): 499–507. http://dx.doi.org/10.1016/j.proeng.2017.04.514.

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Schick, Yannik, Guilherme H. Weber, Marco Da Silva, Cicero Martelli, and Mark W. Hlawitschka. "Flow monitoring in a bubble column reactor by Distributed Acoustic Sensing." tm - Technisches Messen 91, s1 (2024): 14–19. http://dx.doi.org/10.1515/teme-2024-0048.

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Zusammenfassung Im Rahmen dieser Publikation berichten wir über den experimentellen Einsatz von Distributed Acoustic Sensing zur Überwachung eines Blasensäulenreaktors. Für diese Art von chemischen Reaktoren gibt es eine Vielzahl von grundlegenden Anwendungen, die eine detaillierte Überwachung der internen Strömungsdynamik erfordern. Im Zuge experimenteller Untersuchungen zeigt Distributed Acoustic Sensing die Fähigkeit, Messungen eines Hydrophons auf nicht-intrusiveWeise zu reproduzieren und mechanische Vibrationsmuster, die mit großen und kleinen Blasen verbunden sind, mit einer hohen räumli
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Becker, Matthew, Thomas Coleman, Christopher Ciervo, Matthew Cole, and Michael Mondanos. "Fluid pressure sensing with fiber-optic distributed acoustic sensing." Leading Edge 36, no. 12 (2017): 1018–23. http://dx.doi.org/10.1190/tle36121018.1.

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10

Hua, Liwei, Xuran Zhu, Baokai Cheng, et al. "Distributed Acoustic Sensing Based on Coherent Microwave Photonics Interferometry." Sensors 21, no. 20 (2021): 6784. http://dx.doi.org/10.3390/s21206784.

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A microwave photonics method has been developed for measuring distributed acoustic signals. This method uses microwave-modulated low coherence light as a probe to interrogate distributed in-fiber interferometers, which are used to measure acoustic-induced strain. By sweeping the microwave frequency at a constant rate, the acoustic signals are encoded into the complex microwave spectrum. The microwave spectrum is transformed into the joint time–frequency domain and further processed to obtain the distributed acoustic signals. The method is first evaluated using an intrinsic Fabry Perot interfer
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11

Douglass, Alexander S., John Ragland, and Shima Abadi. "Overview of distributed acoustic sensing technology and recently acquired data sets." Journal of the Acoustical Society of America 153, no. 3_supplement (2023): A64. http://dx.doi.org/10.1121/10.0018174.

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Fiber optic distributed acoustic sensing (DAS) is a recent innovation utilized primarily in the seismic community for measuring seismic acoustics signals at low frequencies (single digit Hz and below). The technique utilizes strain rates in a fiber optic cable, observed via the backscatter of light pulses, to measure the acoustic field. Recently, the capabilities of this technology to measure higher frequency acoustic fields (10s to 100s of Hz) have been explored. Low frequency marine mammals calls at ∼20 Hz and ship noises have been successfully recorded, and a recent experiment demonstrated
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Su, Yuqi, Fusang Zhang, Kai Niu, et al. "Embracing Distributed Acoustic Sensing in Car Cabin for Children Presence Detection." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 8, no. 1 (2024): 1–28. http://dx.doi.org/10.1145/3643548.

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Contactless acoustic sensing has been actively exploited in the past few years to enable a large range of applications, ranging from fine-grained vital sign monitoring to coarse-grained human tracking. However, existing acoustic sensing systems mainly work on smartphone or smart speaker platforms. In this paper, we envision an exciting new acoustic sensing platform, i.e., car cabin which is inherently embedded with a large number of speakers and microphones. We propose the new concept of distributed acoustic sensing and develop novel designs leveraging the unique characteristics of rich multi-
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13

Zhou, Ran, Konstantin Osypov, Andrej Bona, et al. "Introduction to special section: Distributed acoustic sensing." Interpretation 9, no. 4 (2021): SJi—SJii. http://dx.doi.org/10.1190/int-2021-0909-spseintro.1.

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14

Gabai, Haniel, and Avishay Eyal. "On the sensitivity of distributed acoustic sensing." Optics Letters 41, no. 24 (2016): 5648. http://dx.doi.org/10.1364/ol.41.005648.

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15

Dreyer, Uilian Jose, Guilherme Dutra, Guilherme Heim Weber, et al. "Horse Gait Identification Using Distributed Acoustic Sensing." IEEE Sensors Journal 21, no. 3 (2021): 3058–65. http://dx.doi.org/10.1109/jsen.2020.3027922.

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16

Lim Chen Ning, Ivan, and Paul Sava. "High-resolution multi-component distributed acoustic sensing." Geophysical Prospecting 66, no. 6 (2018): 1111–22. http://dx.doi.org/10.1111/1365-2478.12634.

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17

Shang, Haiyan, Lin Zhang, and Shaoyi Chen. "Field Experiments of Distributed Acoustic Sensing Measurements." Photonics 11, no. 11 (2024): 1083. http://dx.doi.org/10.3390/photonics11111083.

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Modern, large bridges and tunnels represent important nodes in transportation arteries and have a significant impact on the development of transportation. The health and safety monitoring of these structures has always been a significant concern and is reliant on various types of sensors. Distributed acoustic sensing (DAS) with telecommunication fibers is an emerging technology in the research areas of sensing and communication. DAS provides an effective and low-cost approach for the detection of various resources and seismic activities. In this study, field experiments are elucidated, using D
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18

Fernández-Ruiz, María R., Marcelo A. Soto, Ethan F. Williams, et al. "Distributed acoustic sensing for seismic activity monitoring." APL Photonics 5, no. 3 (2020): 030901. http://dx.doi.org/10.1063/1.5139602.

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19

Poletto, Flavio, Daniel Finfer, Piero Corubolo, and Biancamaria Farina. "Dual wavefields from distributed acoustic sensing measurements." GEOPHYSICS 81, no. 6 (2016): D585—D597. http://dx.doi.org/10.1190/geo2016-0073.1.

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Distributed acoustic sensing (DAS) using fiber optic cables is an emerging seismic acquisition technology for the oil and gas industry, geothermal resource exploration, and underground fluid-storage monitoring. This technology offers the advantage of improving seismic acquisition by enabling massive arrays for monitoring of seismic wavefields at reduced cost with respect to conventional methods. In general, it is accepted that this method provides acoustic signals comparable with conventional seismic data, however, without the multicomponent directional information typical of geophones. We hav
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20

Lim Chen Ning, Ivan, and Paul Sava. "Multicomponent distributed acoustic sensing: Concept and theory." GEOPHYSICS 83, no. 2 (2018): P1—P8. http://dx.doi.org/10.1190/geo2017-0327.1.

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Distributed acoustic sensing (DAS) data are increasingly used in geophysics. Lower in cost and higher in spatial resolution, DAS data are appealing, especially in boreholes in which optical fibers are readily available. DAS has the potential to become a permanent reservoir monitoring tool with a reduced sensing time interval. To accomplish this goal, it is critical that DAS can record all wave modes to fully characterize reservoir properties. This goal can be achieved by recording the complete strain tensor consisting of 6C. Conventional DAS provides projections of these components along the o
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21

Liu, Xiaohui, Chen Wang, Ying Shang, et al. "Distributed acoustic sensing with Michelson interferometer demodulation." Photonic Sensors 7, no. 3 (2016): 193–98. http://dx.doi.org/10.1007/s13320-017-0363-y.

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22

Xie, Zhiyuan, Yuwei Sun, Anqiang Lv, and Qian Xu. "Measurement and Evaluation Method of Distributed Optical Fiber Acoustic Sensing Performance." Photonics 11, no. 2 (2024): 166. http://dx.doi.org/10.3390/photonics11020166.

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Distributed acoustic sensing incorporates multiple indicators, and there exists a mutually constraining relationship among these indicators. Different application fields have varying requirements for indicators. Therefore, indicator testing and comprehensive evaluations are crucial for engineering applications. In this paper, we conducted a theoretical analysis of key indicators, including frequency response, sensitivity, spatial resolution, sensing distance, multi-point perturbation, and temperature influence. The indicator test scheme was developed, and a test system was constructed. The tes
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23

Jiajing, Liang, Wang Zhaoyong, Lu Bin, et al. "Distributed acoustic sensing for 2D and 3D acoustic source localization." Optics Letters 44, no. 7 (2019): 1690. http://dx.doi.org/10.1364/ol.44.001690.

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24

Ragland, John, Alexander S. Douglass, and Shima Abadi. "Using distributed acoustic sensing for ocean ambient sound analysis." Journal of the Acoustical Society of America 153, no. 3_supplement (2023): A64. http://dx.doi.org/10.1121/10.0018176.

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Distributed acoustic sensing (DAS) is a technique that utilizes the back scattering in fiber optic cables to densely sample the strain rate in both space and time. This technique has been widely demonstrated as a powerful tool for seismic sensing, but the efficacy of submerged, under-sea cables for ocean acoustic sensing remains underexplored. The ocean observatories initiative (OOI) conducted a distributed acoustic sensing experiment in November of 2021, where two of the fiber optic cables continuously recorded the strain rate for four days. In this talk, the ambient sound field recorded by t
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25

SAM, A. ROBERT, G. PUNITHAVATHY, and G. S. AYYAPPAN. "Distributed Acoustic Sensing Signal Model Under Static Fiber Conditions." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 08 (2024): 1–6. http://dx.doi.org/10.55041/ijsrem36976.

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This paper presents a statistical model for distributed acoustic sensor interrogation units that utilizes laser pulses transmitted into fiber optics. Interactions within the fiber lead to localized acoustic energy, resulting in backscatter, which is a reflection of the light. Explicit equations were used to calculate the amplitudes and phases of backscattered signals. The proposed model accurately predicts the amplitude signal spectrum and autocorrelation, aligning well with experimental observations. This study also explores the phase signal characteristics relevant to optical time-domain ref
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Li, Wenmin, Yang Lu, Yu Chen, Yan Liang, and Zhou Meng. "Directivity Research of Sensing Channels in a Distributed Fiber Optic Hydrophone." Journal of Physics: Conference Series 2486, no. 1 (2023): 012082. http://dx.doi.org/10.1088/1742-6596/2486/1/012082.

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Abstract An acoustic orientation method using the directivity of sensing channels in distributed fiber optic hydrophone (DFOH) is presented and demonstrated. Theoretical analysis shows that the sensing channel of DFOH is directional. Based on the directivity function of the channel, the direction of the acoustic signal can be obtained by scanning the length of the sensing channel, which is confirmed by experiments.
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Haile, Mulugeta A., Nathaniel E. Bordick, and Jaret C. Riddick. "Distributed acoustic emission sensing for large complex air structures." Structural Health Monitoring 17, no. 3 (2017): 624–34. http://dx.doi.org/10.1177/1475921717714614.

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The vast majority of existing work on acoustic emission–based structural health monitoring is for geometrically simple structures with uninterrupted propagation path and constant wave speed. Realistic systems such as a full-scale fuselage, however, are built from interconnected pieces of acoustically mismatched parts such as sandwich core panels, stringer stiffened skin, and fastener holes. The geometric complexity and dynamic operating environment of realistic systems mean that the acoustic emission wave undergoes multiple reflections, refractions, and mode changes resulting in overlapped tra
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Chen, Wenjie, Junfeng Jiang, Kun Liu, et al. "Self-copy-shift-based differential phase extracting method for fiber distributed acoustic sensing." Chinese Optics Letters 18, no. 8 (2020): 081201. http://dx.doi.org/10.3788/col202018.081201.

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Abadi, Shima, Alexander S. Douglass, and John Ragland. "Comparing distributed acoustic sensing data with hydrophone recordings." Journal of the Acoustical Society of America 153, no. 3_supplement (2023): A64. http://dx.doi.org/10.1121/10.0018175.

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Distributed acoustic sensing (DAS) is a technology that transforms telecommunication fiber optic cables into dense sensor arrays by continuously transmitting pulses of light down the cable and measuring backscattering from natural inhomogeneities within the fiber cable. The technology can densely sample the acoustic field over long ranges (up to 100 km), providing a means for large scale passive acoustic monitoring. To evaluate the capabilities of DAS, it is necessary to benchmark and calibrate the technology relative to traditional hydrophone data. The DAS Calibration Experiment 2022 (DASCAL2
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Geary, Andrew. "Seismic Soundoff: What geophysicists and engineers need to know about DAS." Leading Edge 41, no. 10 (2022): 740. http://dx.doi.org/10.1190/tle41100740.1.

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In this episode, Mark Willis discusses his Distinguished Instructor Short Course, “Distributed acoustic sensing for seismic measurements — What geophysicists and engineers need to know.” Willis helps attendees build intuition and understanding of the value, limitations, and applications of distributed acoustic sensing (DAS) seismic technology. Hear the full episode at https://seg.org/podcast/post/15802 .
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Turov, Artem T., Yuri A. Konstantinov, D. Claude, et al. "Comparison of the Sensitivity of Various Fibers in Distributed Acoustic Sensing." Applied Sciences 14, no. 22 (2024): 10147. http://dx.doi.org/10.3390/app142210147.

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Standard single-mode telecommunication optical fiber is still one of the most popular in distributed acoustic sensing. Understanding the acoustic, mechanical and optical features of various fibers available currently can lead to a better optimization of distributed acoustic sensors, cost reduction and adaptation for specific needs. In this paper, a study of the performances of seven fibers with different coatings and production methods in a distributed acoustic sensor setup is presented. The main results include the amplitude–frequency characteristic for each of the investigated fibers in the
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Sun, Yixiang, Hao Li, Cunzheng Fan, et al. "Review of a Specialty Fiber for Distributed Acoustic Sensing Technology." Photonics 9, no. 5 (2022): 277. http://dx.doi.org/10.3390/photonics9050277.

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Specialty fibers have introduced new levels of flexibility and variability in distributed fiber sensing applications. In particular, distributed acoustic sensing (DAS) systems utilized] the unique functions of specialty fibers to achieve performance enhancements in various distributed sensing applications. This paper provides an overview of recent preparations and developments of specialty-fiber-based DAS systems and their sensing applications. The specialty-fiber-based DAS systems are categorized and reviewed based on the differences in scattering enhancement and methods of preparation. The p
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Le Calvez, Joël, and Erkan Ay. "Introduction to this special section: Fiber optics." Leading Edge 43, no. 11 (2024): 719. http://dx.doi.org/10.1190/tle43110719.1.

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Fiber-optic technology has revolutionized various fields, including telecommunications, medicine, and geophysics. One of the most promising advancements within fiber optics is distributed sensing, which enables the continuous measurement (versus space-limited point sensing) of physical parameters over long distances. Distributed temperature, strain, acoustic, and pressure sensing (DxS) are cutting-edge technologies that revolutionize the way we monitor and analyze temperature, acoustic, and pressure signals over large distances. Unlike traditional sensors, DxS utilizes optical fibers as sensit
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Gu Jinfeng, 顾金凤, 卢斌 Lu Bin, 杨竣淇 Yang Junqi, et al. "Distributed Acoustic Sensing Based on Multi-Core Fiber." Acta Optica Sinica 41, no. 7 (2021): 0706003. http://dx.doi.org/10.3788/aos202141.0706003.

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35

Costley, Richard D., Gustavo Galan-Comas, Kent K. Hathaway, Stephen A. Ketcham, and Clay K. Kirkendall. "Distributed acoustic sensing for near-surface seismic applications." Journal of the Acoustical Society of America 144, no. 3 (2018): 1702–3. http://dx.doi.org/10.1121/1.5067562.

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Mateeva, Albena, Jorge Lopez, Jeff Mestayer, et al. "Distributed acoustic sensing for reservoir monitoring with VSP." Leading Edge 32, no. 10 (2013): 1278–83. http://dx.doi.org/10.1190/tle32101278.1.

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Madsen, Karen Nørgaard, Richard Tøndel, and Øyvind Kvam. "Data-driven depth calibration for distributed acoustic sensing." Leading Edge 35, no. 7 (2016): 610–14. http://dx.doi.org/10.1190/tle35070610.1.

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Nishiguchi, Ken’ichi. "Phase unwrapping for fiber-optic distributed acoustic sensing." Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 2016 (2016): 81–87. http://dx.doi.org/10.5687/sss.2016.81.

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Dagallier, Adrien, Sylvain Cheinet, Daniel Juvé, Timothée Surgis, and Thierry Broglin. "Distributed acoustic sensing of shots in realistic environments." Journal of the Acoustical Society of America 146, no. 4 (2019): 2906. http://dx.doi.org/10.1121/1.5137082.

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40

Konsbruck, Robert L., Emre Telatar, and Martin Vetterli. "On Sampling and Coding for Distributed Acoustic Sensing." IEEE Transactions on Information Theory 58, no. 5 (2012): 3198–214. http://dx.doi.org/10.1109/tit.2012.2184849.

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Bona, Andrej, and Roman Pevzner. "Distributed Acoustic Sensing for Mineral Exploration: Case Study." ASEG Extended Abstracts 2018, no. 1 (2018): 1–4. http://dx.doi.org/10.1071/aseg2018abw8_4f.

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Martins, Wallace A., Marcello L. R. de Campos, Rafael da Silva Chaves, et al. "Communication Models for Distributed Acoustic Sensing for Telemetry." IEEE Sensors Journal 17, no. 15 (2017): 4677–88. http://dx.doi.org/10.1109/jsen.2017.2714023.

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Zhu, Tieyuan, Ariel Lellouch, and Kyle T. Spikes. "Introduction to this special section: Distributed acoustic sensing." Leading Edge 39, no. 11 (2020): 775. http://dx.doi.org/10.1190/tle39110775.1.

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Distributed acoustic sensing (DAS) has seen many advances in recent years with many different applications. This special section contains six papers featuring applications that vary from microseismic event detection to subsea applications to surface deployments, fracture characterization, and well irregularity identification. Each paper introduces a unique problem and then poses the use of DAS in an appropriate way to solve the problem. Special sections on DAS are relatively frequent in the literature currently, so these papers are a snapshot of the work done with the technology. We hope you e
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Yang, Jihyun, Jeffrey Shragge, and Ge Jin. "Filtering Strategies for Deformation-Rate Distributed Acoustic Sensing." Sensors 22, no. 22 (2022): 8777. http://dx.doi.org/10.3390/s22228777.

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Deformation-rate distributed acoustic sensing (DAS), made available by the unique designs of certain interrogator units, acquires seismic data that are theoretically equivalent to the along-fiber particle velocity motion recorded by geophones for scenarios involving elastic ground-fiber coupling. While near-elastic coupling can be achieved in cemented downhole installations, it is less obvious how to do so in lower-cost horizontal deployments. This investigation addresses this challenge by installing and freezing fiber in shallow backfilled trenches (to 0.1 m depth) to achieve improved couplin
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Chambers, Derrick, Alexander Ankamah, Ahmad Tourei, et al. "Distributed acoustic sensing (DAS) for longwall coal mines." International Journal of Rock Mechanics and Mining Sciences 189 (May 2025): 106090. https://doi.org/10.1016/j.ijrmms.2025.106090.

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Su, Yuqi, Fusang Zhang, Beihong Jin, and Daqing Zhang. "Manipulation of Acoustic Focusing for Multi-target Sensing with Distributed Microphones in Smart Car Cabin." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 9, no. 2 (2025): 1–28. https://doi.org/10.1145/3729470.

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Smart car cabins have drawn great attention in the past few years to enable a wide range of applications, including in-car entertainment, road noise cancellation, and voice control. These applications have been underpinned by the addition of a very large number of acoustic modules in the cabin, which has further opened up new opportunities for acoustic contactless sensing in smart cabins. Different from the traditional smartphone or smart speaker for acoustic sensing, in this paper, we envision to manipulate the inherently embedded speakers and microphones in car cabin to produce 3D spatial si
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47

Ershov, Ivan, and Oleg Stukach. "Seismic Field Tests of a Distributed Acoustic Sensor." Systems Engineering and Infocommunications, no. 1 (March 31, 2025): 17–21. https://doi.org/10.5281/zenodo.15110964.

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This research is some contribution to advancing acoustic sensing, offering long-range monitoring of boreholes. High sensitive distributed acoustic sensor is required in oil and gas exploration, pipeline detection, and various practical applications. In this paper, a high sensitive quasi distributed acoustic sensor was tested in borehole. The waveforms are presented and distributed audio signal and spatial acoustic imaging are demonstrated. The field test results of the sound detection illustrate a good sensitivity within the flat frequency range up to 5 kHz up to 900 m depth. The partial resul
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Goestchel, Quentin, William S. D. Wilcock, and Shima Abadi. "Enhancing fin whale vocalizations in distributed acoustic sensing data." Journal of the Acoustical Society of America 157, no. 5 (2025): 3655–66. https://doi.org/10.1121/10.0036696.

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Detecting and locating marine mammals is essential for understanding their behavior and supporting conservation efforts. Acoustic methods complement visual surveys and tagging, which are often limited in spatial and temporal coverage. Fin whales are particularly suited for acoustic monitoring due to their stereotypical 20 Hz vocalizations. Distributed Acoustic Sensing (DAS) offers a promising addition to hydrophone data, using fiber-optic cables as sensors for continuous, high-resolution monitoring over distances up to about 100 km. In November 2021, a DAS dataset was collected using the Ocean
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Dejneka, Zach, Daniel Homa, Joshua Buontempo, et al. "Magnetic Field Sensing via Acoustic Sensing Fiber with Metglas® 2605SC Cladding Wires." Photonics 11, no. 4 (2024): 348. http://dx.doi.org/10.3390/photonics11040348.

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Magnetic field sensing has the potential to become necessary as a critical tool for long-term subsurface geophysical monitoring. The success of distributed fiber optic sensing for geophysical characterization provides a template for the development of next generation downhole magnetic sensors. In this study, Sentek Instrument’s picoDAS is coupled with a multi-material single mode optical fiber with Metglas® 2605SC cladding wire inclusions for magnetic field detection. The response of acoustic sensing fibers with one and two Metglas® 2605SC cladding wires was evaluated upon exposure to lateral
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Yun, Changho. "Underwater Multi-Channel MAC with Cognitive Acoustics for Distributed Underwater Acoustic Networks." Sensors 24, no. 10 (2024): 3027. http://dx.doi.org/10.3390/s24103027.

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Abstract:
The advancement of underwater cognitive acoustic network (UCAN) technology aims to improve spectral efficiency and ensure coexistence with the underwater ecosystem. As the demand for short-term underwater applications operated under distributed topologies, like autonomous underwater vehicle cluster operations, continues to grow, this paper presents Underwater Multi-channel Medium Access Control with Cognitive Acoustics (UMMAC-CA) as a suitable channel access protocol for distributed UCANs. UMMAC-CA operates on a per-frame basis, similar to the Multi-channel Medium Access Control with Cognitive
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