Fibre-Optic Cable Types and Installations

Fiber Optics ◽  
2006 ◽  
pp. 79-94
Keyword(s):  
Fibre Optic ◽  
Fibre Optic Cable

Myth: Light Travels to and from the Sample in a Fibre-Optic Cable without Problems

NIR news ◽  
2014 ◽  
Vol 25 (6) ◽  
pp. 25-26 ◽  
Author(s):  
Kim H. Esbensen ◽  
Paul Geladi ◽  
Anders Larsen
Keyword(s):  
Fibre Optic ◽  
Fibre Optic Cable

scholarly journals Fibre-Optic Cable Types and Installations

Photonics ◽  
2017 ◽  
pp. 513-528
Author(s):  
Abdul Al-Azzawi
Keyword(s):  
Fibre Optic ◽  
Fibre Optic Cable

Wave-selective beamforming with Distributed Acoustic Sensing

2021 ◽  
Author(s):  
Daniel C. Bowden ◽  
Sara Klaasen ◽  
Eileen Martin ◽  
Patrick Paitz ◽  
Andreas Fichtner
Keyword(s):  
Real Data ◽  
Primary Sources ◽  
Seismic Sources ◽  
Fibre Optic ◽  
Wave Type ◽  
Matched Field Processing ◽  
Fibre Optic Cable ◽  
Secondary Scattering ◽  
Distributed Acoustic Sensing ◽  
Beamforming Algorithm

<p>As fibre-optic DAS deployments become more common, researchers are turning to tried-and-true methods of locating or characterizing seismic sources such as beamforming. However, the strain measurement from DAS intrinsically carries its own sensitivities to both wave type and polarization (Martin et al. 2018, Paitz 2020 doctoral thesis). Additionally, a measurement along a conventional fibre-optic cable only provides one component of motion, and so certain azimuths may be blind to certain types of seismic sources, unless the cable layout can be designed to be oriented in multiple directions.</p><p>In this work, we explore the development and application of a beamforming algorithm that explicitly searches for multiple wavetypes. This builds on 3-component beamforming or Matched Field Processing (MFP) algorithms by Riahi et al. (2013), and Gal et al. (2018), where in addition to gridsearching over possible source azimuths, a distinct gridsearch is performed for each possible wavetype of interest. This does not solve the problem that a given cable orientation might be less sensitive to certain directions, but at least an array-response function can be robustly defined for each type of seismic excitation. This might help further distinguish whether beamforming observations are dominated by primary sources or by secondary scattering (van der Ende and Ampuero, 2020 preprint).</p><p>Much of this work uses analytic theory and synthetic examples. Time permitting, the enhanced algorithm will also be applied to data from the Mt. Meager experiment to explore its feasibility and efficacy with real data (EGU contribution from Klaasen et. al, 2021).</p>

Fibre-optic cable for CO and CO2 laser power transmission

1985 ◽  
Vol 17 (4) ◽  
pp. 213-214 ◽  
Author(s):  
V.S. Alejnikov ◽  
V.G. Artjushenko ◽  
V.P. Belyaev ◽  
V.V. Vojtsekhovsky ◽  
E.M. Dianov ◽  
...  
Keyword(s):  
Co2 Laser ◽  
Laser Power ◽  
Power Transmission ◽  
Fibre Optic ◽  
Fibre Optic Cable

Danish earthquake recorded by distributed acoustic sensing (DAS)

2020 ◽  
Author(s):  
Camilla Rasmussen ◽  
Peter H. Voss ◽  
Trine Dahl-Jensen
Keyword(s):  
Field Test ◽  
Signal To Noise Ratio ◽  
Field Tests ◽  
Small Subset ◽  
Fibre Optic ◽  
Data Set ◽  
Acoustic Sensing ◽  
Arrival Times ◽  
Fibre Optic Cable ◽  
Distributed Acoustic Sensing

<p>On September 16th 2018 a Danish earthquake of local magnitude 3.7 was recorded by distributed acoustic sensing (DAS) in a ~23 km long fibre-optic cable. The data are used to study how well DAS can be used as a supplement to conventional seismological data in earthquake localisation. One of the goals in this study is extracting a small subset of traces with clear P and S phases to use in an earthquake localisation, from the 11144 traces the DAS system provide. The timing in the DAS data might not be reliable, and therefore differences in arrival times of S and P are used instead of the exact arrival times. <br>The DAS data set is generally noisy and with a low signal-to-noise ratio (SNR). It is examined whether stacking can be used to improve SNR. The SNR varies a lot along the fibre-optic cable, and at some distances, it is so small that the traces are useless. Stacking methods for improving SNR are presented.</p><p>A field test at two location sites of the fibre-optic cable was conducted with the purpose of comparing DAS data with seismometer data. At the field sites, hammer shots were recorded by a small array of three STS-2 sensors located in a line parallel to the fibre-optic cable. The recordings generally show good consistency between the two data sets. <br>In addition, the field tests are used to get a better understanding of the noise sources in the DAS recording of the earthquake. There are many sources of noise in the data set. The most prominent are a line of windmills that cross the fibre-optic cable and people walking in the building where the detector is located. Also, the coupling between the fibre-optic cable and the ground varies along the cable length due to varying soil type and wrapping around the fibre-optic cable, which is also evident in field test data. Furthermore, the data from the field tests are used to calibrate the location of the fibre-optic cable, which is necessary for using the DAS data in an earthquake localisation. <br>Data processing is done in Matlab and SEISAN.</p>

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