scholarly journals Distributed Acoustic Sensing Based on Coherent Microwave Photonics Interferometry

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6784
Author(s):  
Liwei Hua ◽  
Xuran Zhu ◽  
Baokai Cheng ◽  
Yang Song ◽  
Qi Zhang ◽  
...  
Keyword(s):  
Michelson Interferometer ◽  
Microwave Frequency ◽  
Microwave Photonics ◽  
Acoustic Signals ◽  
Microwave Spectrum ◽  
Acoustic Sensing ◽  
Time Frequency ◽  
Constant Rate ◽  
Distributed Acoustic Sensing ◽  
Acoustic Sources

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 interferometer (IFPI). Acoustic signals of frequency up to 15.6 kHz were detected. The method was further demonstrated using an array of in-fiber weak reflectors and an external Michelson interferometer. Two piezoceramic cylinders (PCCs) driven at frequencies of 1700 Hz and 3430 Hz were used as acoustic sources. The experiment results show that the sensing system can locate multiple acoustic sources. The system resolves 20 nε when the spatial resolution is 5 cm. The recovered acoustic signals match the excitation signals in frequency, amplitude, and phase, indicating an excellent potential for distributed acoustic sensing (DAS).

scholarly journals Distributed Acoustic Sensing Based on Coherent Microwave Photonics Interferometry

2021 ◽  
Author(s):  
Liwei Hua ◽  
Xuran Zhu ◽  
Baokai Cheng ◽  
Yang Song ◽  
Qi Zhang ◽  
...  
Keyword(s):  
Michelson Interferometer ◽  
Microwave Frequency ◽  
Microwave Photonics ◽  
Acoustic Signals ◽  
Microwave Spectrum ◽  
Acoustic Sensing ◽  
Time Frequency ◽  
Constant Rate ◽  
Distributed Acoustic Sensing ◽  
Acoustic Sources

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 interferometer (IFPI). Acoustic signals of frequency up to 15.6 kHz were detected. The method was further demonstrated using an array of in-fiber weak reflectors and an external Michelson interferometer. Two piezo-ceramic cylinders (PCCs) driven at frequencies of 1700 Hz and 3430 Hz were used as acoustic sources. The experiment results show that the sensing system can locate multiple acoustic sources. The system resolves 20 nε when the spatial resolution is 5 cm. The recovered acoustic signals match the excitation signals in frequency, amplitude, and phase, indicating an excellent potential for distributed acoustic sensing (DAS).

scholarly journals Distributed acoustic sensing with Michelson interferometer demodulation

2016 ◽  
Vol 7 (3) ◽  
pp. 193-198 ◽  
Author(s):  
Xiaohui Liu ◽  
Chen Wang ◽  
Ying Shang ◽  
Chang Wang ◽  
Wenan Zhao ◽  
...  
Keyword(s):  
Michelson Interferometer ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing

Combining Distributed Acoustic Sensing and Beamforming in a Volcanic Environment on Mount Meager, British Columbia.

2021 ◽  
Author(s):  
Sara Klaasen ◽  
Patrick Paitz ◽  
Jan Dettmer ◽  
Andreas Fichtner
Keyword(s):  
British Columbia ◽  
Power Distribution ◽  
High Frequency ◽  
Low Frequency ◽  
Volcanic Tremor ◽  
Extreme Environment ◽  
Volcanic Complex ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing ◽  
Volcanic Environment

<p>We present one of the first applications of Distributed Acoustic Sensing (DAS) in a volcanic environment. The goals are twofold: First, we want to examine the feasibility of DAS in such a remote and extreme environment, and second, we search for active volcanic signals of Mount Meager in British Columbia (Canada). </p><p>The Mount Meager massif is an active volcanic complex that is estimated to have the largest geothermal potential in Canada and caused its largest recorded landslide in 2010. We installed a 3-km long fibre-optic cable at 2000 m elevation that crosses the ridge of Mount Meager and traverses the uppermost part of a glacier, yielding continuous measurements from 19 September to 17 October 2019.</p><p>We identify ~30 low-frequency (0.01-1 Hz) and 3000 high-frequency (5-45 Hz) events. The low-frequency events are not correlated with microseismic ocean or atmospheric noise sources and volcanic tremor remains a plausible origin. The frequency-power distribution of the high-frequency events indicates a natural origin, and beamforming on these events reveals distinct event clusters, predominantly in the direction of the main peaks of the volcanic complex. Numerical examples show that we can apply conventional beamforming to the data, and that the results are improved by taking the signal-to-noise ratio of individual channels into account.</p><p>The increased data quantity of DAS can outweigh the limitations due to the lower quality of individual channels in these hazardous and remote environments. We conclude that DAS is a promising tool in this setting that warrants further development.</p>

Capturing Glacier-Wide Cryoseismicity With Distributed Acoustic Sensing

2021 ◽  
Author(s):  
Fabian Walter ◽  
Patrick Paitz ◽  
Andreas Fichtner ◽  
Pascal Edme ◽  
Wojciech Gajek ◽  
...  
Keyword(s):  
Fiber Optic ◽  
Flow Line ◽  
Ground Deformation ◽  
Sensor Coverage ◽  
Mountain Glacier ◽  
Acoustic Sensing ◽  
Alpine Glacier ◽  
Glacier Ice ◽  
Distributed Acoustic Sensing ◽  
Ice Sheet Dynamics

<p>Over the past 1-2 decades, seismological measurements have provided new and unique insights into glacier and ice sheet dynamics. At the same time, sensor coverage is typically limited in harsh glacial environments with littile or no access. Turning kilometer-long fiber optic cables placed on the Earth’s surface into thousands of seismic sensors, Distributed Acoustic Sensing (DAS) may overcome the limitation of sensor coverage in the cryosphere.</p><p>First DAS applications on the Greenland and Antarctic ice sheets and on Alpine glacier ice have highlighted the technique’s superiority. Signals of natural and man-made seismic sources can be resolved with an unrivaled level of detail. This offers glaciologists new perspectives to interpret their seismograms in terms of ice structure, basal boundary conditions and source locations. However, previous studies employed only relatively small network scales with a point-like borehole deployment or < 1 km cable aperture at the ice surface.</p><p>Here we present a DAS installation, which aims to cover the majority of an Alpine glacier catchment: For one month in summer 2020 we deployed a 9 km long fiber optic cable on Rhonegletscher, Switzerland, and gathered continuous DAS data. The cable followed the glacier’s central flow line starting in the lowest kilometer of the ablation zone and extending well into the accumulation area. Even for a relatively small mountain glacier such as Rhonegletscher, cable deployment was a considerable logistical challenge. However, initial data analysis illustrates the benefit compared to conventional cryoseismological instrumentation: DAS measurements capture ground deformation over many octaves, including typical high-frequency englacial sources (10s to 100s of Hz) related to crevasse formation and basal sliding as well as long period signals (10s to 100s of seconds) of ice deformation. Depending on the presence of a snow cover, DAS records contain strong environmental noise (wind, meltwater flow, precipitation) and thus exhibit lower signal-to-noise ratios compared to conventional on-ice seismic installations. This is nevertheless outweighed by the advantage of monitoring ground unrest and ice deformation of nearly an entire glacier. We present a first compilation of signal and noise records and discuss future directions to leverage DAS data sets in glaciological research.</p><p> </p><p> </p><p> </p>

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