Distributed sensing of microseisms and teleseisms with submarine dark fibers

Fading suppression method based on redundant data within the spatial resolution and deep learning for a Φ-OTDR system

Weak light intensity positions induced by interference fading adversely affect the sensing performance of phase-sensitive optical time-domain reflectometry (Φ-OTDR). Most effective fading suppression methods rely on frequency or phase modulation of the light source, which requires complex hardware modifications. To solve the above issue, this paper proposes a novel multi-channel data synthesizing method based on deep neural network (MDS-DNN) to reduce the impact of interference fading on the signal-to-noise ratio (SNR) of Φ-OTDR. The proposed algorithm can work efficiently without any modification of the conventional Φ-OTDR setup. The spatial sampling rate of the Φ-OTDR systems is typically much higher than the spatial resolution. This means that neighboring sampling points carry the same external vibration signal, providing redundant information. Therefore, it is possible to perform comprehensive analysis on these multi-channel data to improve the suppression capability of interference fading noise. This work designs a long short-term memory (LSTM) network-based framework and an end-to-end training strategy to automatically learn the correlation between these multi-channel data and the ideal sensing signal. Simulation and experimental results show that the MDS-DNN algorithm can effectively suppress phase noise and improve the SNR at fading positions. Experiments using the data collected from the actual Φ-OTDR system demonstrate that the output SNR can reach 49.88 dB, which is 19.65 dB higher than the average level of the input channels. Moreover, the MDS-DNN method reduces the false alarm rate caused by interference fading by one order.

Laser interferometry for high-speed railway health inspection using telecom fiber along the line

The health inspection of widespread high-speed railway network is crucial to maintain the regular transportation, particularly as the velocity of high-speed trains continues to escalate. To narrow the long inspection period of current track recording vehicle method, we have implemented a laser interferometer sensing system to turn those existing fiber cables within high-speed railway cable ducts into effective sensing elements. Based on the distributed vibration sensing of daily passing trains, an average power spectrum density indicator is used to assess the health of high-speed railway infrastructures. During the observation over one year, average power spectrum densities of 4 typical infrastructures remain stable, indicating their robust health despite challenging environmental conditions. To demonstrate the sensitivity of average power spectrum density indicator on railway faults, we analyze the sensing results of a rail section before and after track maintenance, which shows distinctive average power spectrum density features corresponding to different levels of creep deformation. Additionally, the sensing system can also report other ambient vibrations, such as seismic waves after propagation of over 300 km. It demonstrates the fiber sensing system not only has the ability to act as a real-time supplementary tool for high-speed railway health inspection, but also has potential to establish a large sensing network.

Enhancing fin whale vocalizations in distributed acoustic sensing data

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 Observatories Initiative Regional Cabled Array, capturing valuable data on fin whale vocalizations. This dataset includes measurements from two cables with 2 m channel spacing, spanning 65-95 km. This study evaluates various approaches-including signal-to-noise ratio estimation, matched filtering, Gabor filtering, and noise envelope subtraction-for enhancing and denoising fin whale calls in DAS data. A method that combines matched filtering and envelope subtraction is most effective at detecting even low SNR fin whale calls and obtaining arrival times. Overall, this study highlights the potential of DAS array processing to significantly improve signal-to-noise ratios and enhance detection capabilities for monitoring fin whales.

Monitoring bands during the Norwegian national day parade: a case study on urban distributed acoustic sensing

Existing networks of fiber optic telecommunication infrastructure can be used to measure acoustic events. For this purpose, a laser instrumentation is attached to a "dark fiber" turning it into a Distributed Acoustic Sensing (DAS) device. In May 2023, a DAS test was conducted to measure acoustic activity in Oslo, Norway. The main purpose was to measure the "pulse" of the Oslo city center during the Norwegian National Day parade. Additionally, five days before and after the National Day were recorded for reference to daily acoustic background noise conditions in Oslo. Data during the National Day captured the yearly parade in which schools and bands participate. Using this data, it was possible to detect the participating bands, analyze their frequency content, and estimate their walking speed and step length. High-order harmonics were recognized in the frequency response for the bands. A total of 88 bands participated in the parade and 87 were detected using the harmonic characteristics. While one individual band could be tracked before the main parade over separate streets, it was challenging to continue the track for other bands within the parade. The test revealed that DAS can be used as part of decision support systems for crowd monitoring.

Local earthquake response on the submarine communication cable in the northern South China Sea

As a new seismological monitoring technology, distributed acoustic sensing (DAS) not only provides a high-precision seismic observation method, but also uses undersea communication fiber or dark fiber to reduce the layout cost, and supports long-term observation for several years, and the sensing resolution reaches the scale of meters. This technique provides a broad prospect for seismic observation in oceanic area which is difficult to be covered by traditional seismic observation instruments. In this paper, we analyzed the DAS waveforms of 10 local-earthquake events waveforms recorded by offshore submarine communication cable in the northern South China Sea, and discussed the response ability of DAS system based on shallow sea communication cable to near-earthquake. It is found that the signals are affected by surface gravitational waves and micro seismic noise (Scholte Wave) generated by solid-liquid coupling motion. Then, waveform stacking, discrete wavelet transform, and empirical mode decomposition are used to denoise the signal in shallow sea area for extracting earthquake waveform. Submarine optical cable is the most widely distributed submarine signal monitoring system in the world. Long-term and cheap deep-sea seismic wave observation based on such the large-scale global ocean observation network can provide important data for the development of seismology.

Study on the spectral characteristics of IF signals and its influence on the performance of heterodyne Φ-OTDR

The heterodyne phase-sensitive optical time-domain reflectometer (Φ-OTDR) is one of the most popular distributed optical fiber sensing (DOFS) technologies due to its high sensitivity, wide frequency response bandwidth, large dynamic range, and resistance to electromagnetic interference. In the signal processing workflow, like the I/Q algorithm, digital filtering of intermediate frequency (IF) signals is unavoidable. This study combines the advantages of the scattering point superposition model and the phase-modulated signal model. Three methods for quasi-matched IF filters are proposed. A signal evaluation system combining Parseval signal-to-noise ratio (Pa-SNR), peak-to-peak value, and signal-to-noise ratio (SNR) is employed. For CIC-type IF filters, it is recommended to cascade no more than 3 low-tap filters. For the variant CIC filter, its demodulation rate is faster than that of the other two filters. But resulted in an SNR of 10 dB lower than the CIC filter, and 15 dB lower than FIR filters because of the asymmetry of IF signals we demonstrated. For FIR-type IF filters, we recommend that the passband cutoff frequency should be at least 2.43 times the reciprocal of the pulse width. This factor decreases with increasing pulse width and narrowing of the transition band, but should not be lower than 1.08. Additionally, it is important to note that within approximately 0.8 times the transition band range of the cutoff frequency, half of the demodulation performance may degrade due to the IF filter passband ripple characteristics.

Measurement of ocean currents by seafloor distributed optical-fiber acoustic sensing

Ocean current measurements play a crucial role in aiding our understanding of ocean dynamics and circulation systems. Traditional methods, such as drifters and ocean buoys, are sparsely distributed and of limited effectiveness due to the nature of the marine environment and high operating expenses. Distributed acoustic sensing (DAS) is an emerging technology using submarine optical-fiber (OF) cables as dense seismo-acoustic arrays, offering a new perspective for ocean observations. Here, in situ observations of ocean surface gravity waves (OSGWs) and ocean currents by DAS were made along a pre-existing 33.6 km seafloor OF cable. The average current velocity and water depth along the cable were determined from observed OSGW-induced seafloor noise (0.05-0.2 Hz) using ambient-noise interferometry and frequency-domain beamforming. Variations in current velocity were derived at high spatiotemporal resolution using the frequency-domain waveform-stretching method. The inverted current velocity was verified by nearby ocean buoy observations and forecasting results. The observations demonstrate the effectiveness of DAS-instrumented OF cables in monitoring ocean currents.

Inclined bending seismic reflection layer in the crust illuminated by distributed fibre-optic-sensing measurements in western Japan

Distributed acoustic sensing (DAS), which enables a single fibre-optic cable to function as multiple sensors, is a technique to measure the strain rate distributed along the cable. This technique is applied to record ground motions in western Japan via a 50 km-long fibre-optic cable beneath a national road. The measured values are strain changes along the cable every 5 m, corresponding to 9788 sensor deployments. This high-density measurement along the long cable successfully recorded the 2021 M2.8 and M3.2 earthquakes that occurred in the crust within the distance of the cable in southern Kyoto. The direct S waves were followed by seismic waves approximately 8-14 s later, which were reflected by lower crustal structures. These waveforms were previously reported by observing many earthquakes via multiple seismometers, but the DAS observations clearly illuminate reflected wavefields from single earthquake observations for the first time. The numerical simulation of the strain-rate wavefields of these earthquakes reveals the existence of a north-dipping thin layer with a slow seismic velocity in the lower crust, which becomes steeper in the shallower part. This layer might represent the path of slab-derived fluid to the shallow fault zone.

High-resolution observations of shallow-water acoustic propagation with distributed acoustic sensing

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 the location accuracy of DAS channels, reducing the location uncertainty to ∼2 m. The DAS array with refined channel positions enables the high-resolution observation of acoustic modal interference. Numerical simulations that reproduce the observed interference pattern suggest a compressional speed of 1750 m/s in the sediment, which is consistent with previous in situ geoacoustic measurements. These findings demonstrate the long-term potential of DAS for high-resolution ocean acoustic studies.

Optical fibre sensing of turbulent-frequency motions in the oceanic environment

Observations of turbulence in the oceanic environment are sparse, with very few cases of coherent measurements with significant spatio-temporal extent due primarily to limitations of current observational tools. Here we propose submarine cables with embedded optical fibres as a potential solution to fill this observational gap, and utilise a recent 12-h observational optical fibre data set from a fast-flowing tidal channel to demonstrate such potential. Firstly, the presence of turbulent-scale signals driven by flow-topography interaction is shown at frequencies of 1 Hz and higher. These signals are consistent with the timing of the tidal flow as recorded by a nearby conventional sensor. Secondly, we show the presence of surface gravity waves with periods of 10 s, which are tight in frequency space further offshore but leak energy into the turbulent frequency range on parts of the cable closer to shore. This is compatible with shoreward-propagating surface waves that break in shallow water. Finally, we fit a theoretical spectral structure to the observations to show that much of the collected data (i) has a spectral slope that is consistent with the turbulent inertial subrange, and (ii) has a range of spectral energy consistent with that expected from turbulence generation by bottom drag acting on the tidal flow. In combination, these results highlight the potential for optical fibre sensing of turbulence, and call for a targeted experiment to characterise the fibre's turbulence-sensing capabilities.

Hybrid fiber-based time synchronization and vibration detection system

We propose a hybrid fiber-based time synchronization and vibration detection system. The vibration is detected by exploring the idle light of the time synchronization system, i.e., the Rayleigh backscattering of the timing pulse disseminated in the fiber link. The addition of a sensing function does not affect the performance of time synchronization. In the multiuser experimental demonstration, time deviation results are 3.6 ps at τ = 1 s and 1.4 ps at τ = 104 s on the 40-km fiber link. Meanwhile, the hybrid system can accurately detect and locate vibrations occurring on the link. This method enables multiple functions of the optical fiber network without occupying extra optical channels. Moreover, it gives a possible solution for enhancing the security of the time synchronization network through vibration detection.

Step-adaptive accelerated demodulation algorithm for LFM-pulse-based distributed acoustic sensing

We propose a novel, to our knowledge, step-adaptive cross-correlation algorithm tailored for distributed acoustic sensing systems based on linear frequency modulation pulses, aiming for rapid demodulation. This algorithm adjusts its step length through an adaptive "successive refinement" search strategy, which greatly improves computational efficiency by reducing the number of cross-correlation computations. Experimental results have shown that the demodulation time can be reduced by approximately 15 times compared to the conventional method, while maintaining the same demodulation result.

Eavesdropping on wastewater pollution: Detecting discharge events from river outfalls via fiber-optic distributed acoustic sensing

Wastewater discharge from outfall pipes can significantly impact river water quality and aquatic ecosystems. Effective outfall monitoring is critical for controlling pollution and protecting public health. This study demonstrates a novel distributed acoustic sensing (DAS) approach for detecting wastewater discharge events from outfall pipes located along rivers. Controlled field experiments were conducted in an industrial park river to systematically evaluate DAS performance. DAS detects vibrational signals imparted to suspended fiber-optic cables by turbulent wastewater flows, predominantly within 10-30 Hz, enabling continuous monitoring along entire river lengths. Vibrational power analysis locates outfalls with meter-level accuracy, while time-frequency techniques discern discharge timing and characteristics. Cable type and outfall-fiber separation influence on detection capability was assessed. Thermoplastic-jacketed tight buffer cables optimized detection through enhanced vibrational coupling. Vibrational energy decreased exponentially with separation, highlighting benefits of proximal deployment for sensitivity. However, detection range scales with discharge flow rate. Frequency centroid proved a robust feature with potential for automated discharge identification. Overall, DAS enables high spatiotemporal resolution monitoring to pinpoint concealed outfalls minimally invasively. This positions DAS as a promising tool supporting improved water governance through early pollution warnings and rapid source localization via outfall vibrational signatures emanating across river networks.

Monitoring ocean currents during the passage of Typhoon Muifa using optical-fiber distributed acoustic sensing

In situ observations under typhoon conditions are sparse and limited. Distributed acoustic sensing (DAS) is an emerging technology that uses submarine optical-fiber (OF) cables to monitor the sea state. Here, we present DAS-based ocean current observations when a super typhoon passed overhead. The microseismic noise induced by ocean surface gravity waves (OSGWs) during Typhoon Muifa (2022) is observed in the ~0.08-0.38 Hz frequency band, with high-frequency (>0.3 Hz) component being tidally modulated. The OSGW propagation along the entire cable is successfully revealed via frequency-wavenumber analysis. Further, a method based on the current-induced Doppler shifts of DAS-recorded OSGW dispersions is proposed to calculate both speeds and directions of horizontal ocean currents. The measured current is consistent with the tidally induced sea-level fluctuations and sea-surface winds observed at a nearby ocean buoy. These observations demonstrate the feasibility of monitoring the ocean current under typhoon conditions using DAS-instrumented cables.

Fading suppression in the Ф-OTDR system based on a phase-modulated optical frequency comb

In this paper, what we believe to be a novel method is proposed to suppress the fading effect of the phase-sensitive optical time domain reflectometer (Ф-OTDR) by using a phase-modulated optical frequency comb. In the Ф-OTDR system, intensity distributions of Rayleigh backscattering (RBS) light are different for pulsed probe lights with different central frequencies, therefore the locations of the fading points corresponding to signals of different frequencies are differently distributed, allowing the use of frequency division multiplexing to suppress the fading effects. In the experimental system of this paper, a continuous light in the form of a frequency comb is firstly generated through phase modulation. It is then modulated into a pulsed probe light and injected into the sensing fiber to produce different RBS intensity distributions. Finally, the extracted phase is processed by using the amplitude evaluation method, so that the distorted phase can be eliminated. Fading suppression is achieved using our system, and the effect of suppression is evaluated. By using an equal-amplitude optical frequency comb containing seven frequency components, the fading probability density of the system is dramatically reduced from the range of 5.49%-9.83% to 0.08%. Compared with the conventional system using a single acoustic-optic modulator to generate the frequency shift, the method proposed in this paper features a larger modulation bandwidth and more flexible frequency combination scheme to better suppress the fading effect. This method does not sacrifice the response bandwidth of the system, and the phase delay can be precisely controlled, which helps to fully suppress the fading effect.

High resolution seafloor thermometry for internal wave and upwelling monitoring using Distributed Acoustic Sensing

Temperature is an essential oceanographic variable (EOV) that still today remains coarsely resolved below the surface and near the seafloor. Here, we gather evidence to confirm that Distributed Acoustic Sensing (DAS) technology can convert tens of kilometer-long seafloor fiber-optic telecommunication cables into dense arrays of temperature anomaly sensors having millikelvin (mK) sensitivity, thus allowing to monitor oceanic processes such as internal waves and upwelling with unprecedented detail. Notably, we report high-resolution observations of highly coherent near-inertial and super-inertial internal waves in the NW Mediterranean sea, offshore of Toulon, France, having spatial extents of a few kilometers and producing maximum thermal anomalies of more than 5 K at maximum absolute rates of more than 1 K/h. We validate our observations with in-situ oceanographic sensors and an alternative optical fiber sensing technology. Currently, DAS only provides temperature changes estimates, however practical solutions are outlined to obtain continuous absolute temperature measurements with DAS at the seafloor. Our observations grant key advantages to DAS over established temperature sensors, showing its transformative potential for the description of seafloor temperature fluctuations over an extended range of spatial and temporal scales, as well as for the understanding of the evolution of the ocean in a broad sense (e.g. physical and ecological). Diverse ocean-oriented fields could benefit from the potential applications of this fast-developing technology.

Submarine optical fiber communication provides an unrealized deep-sea observation network

Oceans are crucial to human survival, providing natural resources and most of the global oxygen supply, and are responsible for a large portion of worldwide economic development. Although it is widely considered a silent world, the sea is filled with natural sounds generated by marine life and geological processes. Man-made underwater sounds, such as active sonars, maritime traffic, and offshore oil and mineral exploration, have significantly affected underwater soundscapes and species. In this work, we report on a joint optical fiber-based communication and sensing technology aiming to reduce noise pollution in the sea while providing connectivity simultaneously with a variety of underwater applications. The designed multifunctional fiber-based system enables two-way data transfer, monitoring marine life and ship movement near the deployed fiber at the sea bottom and sensing temperature. The deployed fiber is equally harnessed to transfer energy that the internet of underwater things (IoUTs) devices can harvest. The reported approach significantly reduces the costs and effects of monitoring marine ecosystems while ensuring data transfer and ocean monitoring applications and providing continuous power for submerged IoUT devices.

Chaos Raman distributed optical fiber sensing

The physics principle of pulse flight positioning is the main theoretical bottleneck that restricts the spatial resolution of the existing Raman distributed optical fiber sensing scheme. Owing to the pulse width of tens of nanoseconds, the spatial resolution of the existing Raman distributed optical fiber sensing scheme with kilometer-level sensing distance is limited to the meter level, which seriously restricts the development of the optical time-domain reflection system. In this paper, a chaos laser is proposed in the context of the physical principle of the Raman scattering effect, and a novel theory of chaos Raman distributed optical fiber sensing scheme is presented. The scheme reveals the characteristics of chaos Raman scattering light excited by a chaotic signal on the sensing fiber. Further, the chaos time-domain compression demodulation mechanism between the temperature variation information and chaos correlation peak is demonstrated. Then, the position of the temperature variation signal is precisely located using the delay time of the chaos correlation peak combined with the chaos pulse flight time. Based on this novel optical sensing mechanism, an experiment with 10 cm spatial resolution and 1.4 km sensing distance was conducted, and the spatial resolution was found to be independent of the sensing distance. Within the limit of the existing spatial resolution theory, the spatial resolution of the proposed scheme is 50 times higher than that of the traditional scheme. The scheme also provides a new research direction for optical chaos and optical fiber sensing.

Broad-bandwidth and accurate optical vibration sensing by using FDM Φ-OTDR with linear regression analysis of multi-frequency phase responses

We demonstrate Φ-OTDR distributed acoustic sensing (DAS) that realizes both a broad bandwidth for the vibration frequency and wide dynamic range for the vibration amplitude based on optical frequency-division-multiplexing (FDM). We enhance the sampling rate of DAS by using FDM while suppressing waveform distortion in time domain (spurious components in spectral domain) caused by sensor nonlinearity inherent in Φ-OTDR, thus improving dynamic range, with linear regression analysis of multi-frequency phase responses. The proposed method compares the phase offsets and responses of each frequency to those of a common reference frequency and uses the information to calibrate each of the different responses. We clarify the physical origin of the problem and the validity of the proposed method in both simulations and experiments. Experimental results show an improvement in dynamic range by above 8 dB on average for vibration waveforms with nɛ-order amplitudes and kHz-order frequencies over 10-km single-mode fiber.

Hybrid Distributed Optical Fiber Sensor for the Multi-Parameter Measurements

Distributed optical fiber sensors (DOFSs) are a promising technology for their unique advantage of long-distance distributed measurements in industrial applications. In recent years, modern industrial monitoring has called for comprehensive multi-parameter measurements to accurately identify fault events. The hybrid DOFS technology, which combines the Rayleigh, Brillouin, and Raman scattering mechanisms and integrates multiple DOFS systems in a single configuration, has attracted growing attention and has been developed rapidly. Compared to a single DOFS system, the multi-parameter measurements based on hybrid DOFS offer multidimensional valuable information to prevent misjudgments and false alarms. The highly integrated sensing structure enables more efficient and cost-effective monitoring in engineering. This review highlights the latest progress of the hybrid DOFS technology for multi-parameter measurements. The basic principles of the light-scattering-based DOFSs are initially introduced, and then the methods and sensing performances of various techniques are successively described. The challenges and prospects of the hybrid DOFS technology are discussed in the end, aiming to pave the way for a vaster range of applications.

Multi-nodes dissemination of stable radio frequency with 10-17 instability over 2000 km optical fiber

To meet the demand of flexible access for high-precision synchronization frequency, we demonstrate multi-node stable radio frequency (RF) dissemination over a long-distance optical fiber. Stable radio frequency signals can be extracted at any node along the optical fiber, not just at the endpoint. The differential mixing structure (DMS) is employed to avoid the frequency harmonic leakage and enhance the precision. The phase-locked loop (PLL) provides frequency reference for the DMS while improving the signal to noise ratio (SNR) of dissemination signal. We measure the frequency instability of multi-node stable frequency dissemination system (MFDS) at different locations along the 2,000 km optical fiber. The measured short-term instability with average time of 1 s are 1.90 × 10-14 @ 500 km, 2.81 × 10-14 @ 1,000 km, 3.46 × 10-14 @ 1,500 km, and 3.84 × 10-14 @ 2,000 km respectively. The long-term instability with average time of 10,000 s are basically the same at any position of the optical fiber, which is about (6.24 ± 0.05) × 10-17. The resulting instability is sufficient for the propagation of precision active hydrogen masers.

Principles and Applications of Seismic Monitoring Based on Submarine Optical Cable

Submarine optical cables, utilized as fiber-optic sensors for seismic monitoring, are gaining increasing interest because of their advantages of extending the detection coverage, improving the detection quality, and enhancing long-term stability. The fiber-optic seismic monitoring sensors are mainly composed of the optical interferometer, fiber Bragg grating, optical polarimeter, and distributed acoustic sensing, respectively. This paper reviews the principles of the four optical seismic sensors, as well as their applications of submarine seismology over submarine optical cables. The advantages and disadvantages are discussed, and the current technical requirements are concluded, respectively. This review can provide a reference for studying submarine cable-based seismic monitoring.

Brillouin-Scattering Induced Noise in DAS: A Case Study

In the paper, the effect of spontaneous Brillouin scattering (SpBS) is analyzed as a noise source in distributed acoustic sensors (DAS). The intensity of the SpBS wave fluctuates over time, and these fluctuations increase the noise power in DAS. Based on experimental data, the probability density function (PDF) of the spectrally selected SpBS Stokes wave intensity is negative exponential, which corresponds to the known theoretical conception. Based on this statement, an estimation of the average noise power induced by the SpBS wave is given. This noise power equals the square of the average power of the SpBS Stokes wave, which in turn is approximately 18 dB lower than the Rayleigh backscattering power. The noise composition in DAS is determined for two configurations, the first for the initial backscattering spectrum and the second for the spectrum in which the SpBS Stokes and anti-Stokes waves are rejected. It is established that in the analyzed particular case, the SpBS noise power is dominant and exceeds the powers of the thermal, shot, and phase noises in DAS. Accordingly, by rejecting the SpBS waves at the photodetector input, it is possible to reduce the noise power in DAS. In our case, this rejection is carried out by an asymmetric Mach-Zehnder interferometer (MZI). The rejection of the SpBS wave is most relevant for broadband photodetectors, which are associated with the use of short probing pulses to achieve short gauge lengths in DAS.

A neural network based global traveltime function (GlobeNN)

Global traveltime modeling is an essential component of modern seismological studies with a whole gamut of applications ranging from earthquake source localization to seismic velocity inversion. Emerging acquisition technologies like distributed acoustic sensing (DAS) promise a new era of seismological discovery by allowing a high-density of seismic observations. Conventional traveltime computation algorithms are unable to handle virtually millions of receivers made available by DAS arrays. Therefore, we develop GlobeNN-a neural network based traveltime function that can provide seismic traveltimes obtained from the cached realistic 3-D Earth model. We train a neural network to estimate the traveltime between any two points in the global mantle Earth model by imposing the validity of the eikonal equation through the loss function. The traveltime gradients in the loss function are computed efficiently using automatic differentiation, while the P-wave velocity is obtained from the vertically polarized P-wave velocity of the GLAD-M25 model. The network is trained using a random selection of source and receiver pairs from within the computational domain. Once trained, the neural network produces traveltimes rapidly at the global scale through a single evaluation of the network. As a byproduct of the training process, we obtain a neural network that learns the underlying velocity model and, therefore, can be used as an efficient storage mechanism for the huge 3-D Earth velocity model. These exciting features make our proposed neural network based global traveltime computation method an indispensable tool for the next generation of seismological advances.

Distributed dynamic strain sensing of very long period and long period events on telecom fiber-optic cables at Vulcano, Italy

Volcano-seismic signals can help for volcanic hazard estimation and eruption forecasting. However, the underlying mechanism for their low frequency components is still a matter of debate. Here, we show signatures of dynamic strain records from Distributed Acoustic Sensing in the low frequencies of volcanic signals at Vulcano Island, Italy. Signs of unrest have been observed since September 2021, with CO₂ degassing and occurrence of long period and very long period events. We interrogated a fiber-optic telecommunication cable on-shore and off-shore linking Vulcano Island to Sicily. We explore various approaches to automatically detect seismo-volcanic events both adapting conventional algorithms and using machine learning techniques. During one month of acquisition, we found 1488 events with a great variety of waveforms composed of two main frequency bands (from 0.1 to 0.2 Hz and from 3 to 5 Hz) with various relative amplitudes. On the basis of spectral signature and family classification, we propose a model in which gas accumulates in the hydrothermal system and is released through a series of resonating fractures until the surface. Our findings demonstrate that fiber optic telecom cables in association with cutting-edge machine learning algorithms contribute to a better understanding and monitoring of volcanic hydrothermal systems.

Phase-sensitive optical time domain reflectometry based on geometric phase measurement

A phase-sensitive optical time domain reflectometer based on coherent heterodyne detection of geometric phase in the beat signal of light, is reported for the first time to our knowledge. The use of the geometric phase to extract strain makes it immune to polarisation diversity fading. This is because a polarisation mismatch between the interfering beams is not a hindrance to its measurement. The geometric phase is calculated using the amplitude of the beat signal and individual beam intensities without any need for phase unwrapping. It is measured per beat period and can be equated with the traditionally measured dynamic phase with appropriate scaling. The results show that the system based on the geometric phase successfully measures strain, free from polarisation mismatch fading and phase unwrapping errors, providing a completely novel solution to these problems.

Distributed Acoustic Sensing Based on Microtremor Survey Method for Near-Surface Active Faults Exploration: A Case Study in Datong Basin, China

Active fault detection has an important significance for seismic disaster prevention and mitigation in urban areas. The high-density station arrays have the potential to provide a microtremor survey solution for shallow seismic investigations. However, the resolution limitation of the nodal seismometer and small-scale lateral velocity being inhomogeneous hinder their application in near-surface active fault exploration. Distributed acoustic sensing (DAS) has been developed rapidly in the past few years; it takes an optical fiber as the sensing medium and signal transmission medium, which can continuously detect vibration over long distances with high spatial resolution and low cost. This paper tried to address the issue of near-surface active fault exploration by using DAS. We selected a normal fault in the southern Datong basin, a graben basin in the Shanxi rift system in north China, to carry out the research. Microtremor surveys across the possible range of the active fault were conducted using DAS and nodal seismometers, so as to obtain a shallow shear wave velocity model. Meanwhile, we applied a Brillouin optical time domain reflectometer (BOTDR) and distributed temperature sensing (DTS) to monitor the real-time fluctuation of ground temperature and strain. Our results show that the resolution of the deep structures of the fault via the microtremor survey based on DAS is lower than that via the seismic reflection; whereas, their fault location is consistent, and the near-surface structure of the fault can be traced in the DAS results. In addition, both the BOTDR and DTS results indicate an apparent consistent change in ground temperature and strain across the fault determined by the DAS result, and the combination of surface monitoring and underground exploration will help to accurately avoid active faults and seismic potential assessment in urban areas.

Distributed acoustic sensing recordings of low-frequency whale calls and ship noise offshore Central Oregon

Distributed acoustic sensing (DAS) is a technique that measures strain changes along an optical fiber to distances of ∼100 km with a spatial sensitivity of tens of meters. In November 2021, 4 days of DAS data were collected on two cables of the Ocean Observatories Initiative Regional Cabled Array extending offshore central Oregon. Numerous 20 Hz fin whale calls, northeast Pacific blue whale A and B calls, and ship noises were recorded, highlighting the potential of DAS for monitoring the ocean. The data are publicly available to support studies to understand the sensitivity of submarine DAS for low-frequency acoustic monitoring.

Integrated sensing and communication in an optical fibre

The integration of high-speed optical communication and distributed sensing could bring intelligent functionalities to ubiquitous optical fibre networks, such as urban structure imaging, ocean seismic detection, and safety monitoring of underground embedded pipelines. This work demonstrates a scheme of integrated sensing and communication in an optical fibre (ISAC-OF) using the same wavelength channel for simultaneous data transmission and distributed vibration sensing. The scheme not only extends the intelligent functionality for optical fibre communication system, but also improves its transmission performance. A periodic linear frequency modulation (LFM) light is generated to act as the optical carrier and sensing probe in PAM4 signal transmission and phase-sensitive optical time-domain reflectometry (Φ-OTDR), respectively. After a 24.5 km fibre transmission, the forward PAM4 signal and the carrier-correspondence Rayleigh backscattering signal are detected and demodulated. Experimental results show that the integrated solution achieves better transmission performance (~1.3 dB improvement) and a larger launching power (7 dB enhancement) at a 56 Gbit/s bit rate compared to a conventional PAM4 signal transmission. Meanwhile, a 4 m spatial resolution, 4.32-nε/[Formula: see text] strain resolution, and over 21 kHz frequency response for the vibration sensing are obtained. The proposed solution offers a new path to further explore the potential of existing or future fibre-optic networks by the convergence of data transmission and status sensing. In addition, such a scheme of using shared spectrum in communication and distributed optical fibre sensing may be used to measure non-linear parameters in coherent optical communications, offering possible benefits for data transmission.

Seismic detection with distributed acoustic sensors using a convolutional neural network in the frequency wavenumber spectrum

With the development of optical fiber distributed acoustic sensors (DAS), their application to seismic observation has become popular. We conducted DAS measurements from November 19 to December 2, 2019, using dark fiber of an ocean bottom cable seismic and tsunami observation system off the Sanriku coast in northeastern Japan and investigated seismic detection methods from the obtained strain rate data. We examined a new seismic detection method using a convolutional neural network, to the best of our knowledge, treating a frequency wavenumber spectrum of strain rate as an image. This method effectively captured a characteristic wave described as the T-phase in a sound fixing and ranging channel even with low signal-to-noise ratio data.

Distributed fiber mountain seismic monitoring and steady-state analysis under natural earthquakes

Mountain dynamic response monitoring plays important roles in geological disaster evolution monitoring and warning. A distributed mountain seismic monitoring and steady-state analysis method is demonstrated with distributed acoustic sensing (DAS) and a natural earthquake stimulus. In the field test, the seismic detection capability is first verified by comparing the recorded seismic waveforms from DAS and existing seismic stations. The vibration signal difference between steady-state and unsteady-state mountain parts is apparent; the operational modal analysis method is utilized to extract the response difference and to monitor the disaster evolution process. The proposed method has many advantages, including being easy to deploy, all-weather online monitoring, etc. It is believed that the proposed method will broaden the DAS application scope and promote the development of geological disaster early warning such as landslides and collapses.

Computer Vision Algorithms of DigitSeis for Building a Vectorised Dataset of Historical Seismograms from the Archive of Royal Observatory of Belgium

Archived seismograms recorded in the 20th century present a valuable source of information for monitoring earthquake activity. However, old data, which are only available as scanned paper-based images should be digitised and converted from raster to vector format prior to reuse for geophysical modelling. Seismograms have special characteristics and specific featuresrecorded by a seismometer and encrypted in the images: signal trace lines, minute time gaps, timing and wave amplitudes. This information should be recognised and interpreted automatically when processing archives of seismograms containing large collections of data. The objective was to automatically digitise historical seismograms obtained from the archives of the Royal Observatory of Belgium (ROB). The images were originallyrecorded by the Galitzine seismometer in 1954 in Uccle seismic station, Belgium. A dataset included 145 TIFF images which required automatic approach of data processing. Software for digitising seismograms are limited and many have disadvantages. We applied the DigitSeis for machine-based vectorisation and reported here a full workflowof data processing. This included pattern recognition, classification, digitising, corrections and converting TIFFs to the digital vector format. The generated contours of signals were presented as time series and converted into digital format (mat files) which indicated information on ground motion signals contained in analog seismograms. We performed the quality control of the digitised traces in Python to evaluate the discriminating functionality of seismic signals by DigitSeis. We shown a robust approach of DigitSeis as a powerful toolset for processing analog seismic signals. The graphical visualisation of signal traces and analysis of the performed vectorisation results shown that the algorithms of data processing performed accurately and can be recommended in similar applications of seismic signal processing in future related works in geophysical research.

A Cost-Effective Distributed Acoustic Sensor for Engineering Geology

A simple and cost-effective architecture of a distributed acoustic sensor (DAS) or a phase-OTDR for engineering geology is proposed. The architecture is based on the dual-pulse acquisition principle, where the dual probing pulse is formed via an unbalanced Michelson interferometer (MI). The necessary phase shifts between the sub-pulses of the dual-pulse are introduced using a 3 × 3 coupler built into the MI. Laser pulses are generated by direct modulation of the injection current, which obtains optical pulses with a duration of 7 ns. The use of an unbalanced MI for the formation of a dual-pulse reduces the requirements for the coherence of the laser source, as the introduced delay between sub-pulses is compensated in the fiber under test (FUT). Therefore, a laser with a relatively broad spectral linewidth of about 1 GHz can be used. To overcome the fading problem, as well as to ensure the linearity of the DAS response, the averaging of over 16 optical frequencies is used. The performance of the DAS was tested by recording a strong vibration impact on a horizontally buried cable and by the recording of seismic waves in a borehole in the seabed.

Filtering Strategies for Deformation-Rate Distributed Acoustic Sensing

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 coupling. This acquisition allows for a reinterpretation of processed deformation-rate DAS waveforms as a "filtered particle velocity" rather than the conventional strain-rate quantity. We present 1D and 2D filtering experiments that suggest 2D velocity-dip filtering can recover improved DAS data panels that exhibit clear surface and refracted arrivals. Data acquired on DAS fibers deployed in backfilled, frozen trenches were more repeatable over a day of acquisition compared to those acquired on a surface-deployed DAS fiber, which exhibited more significant amplitude variations and lower signal-to-noise ratios. These observations suggest that deploying fiber in backfilled, frozen trenches can help limit the impact of environmental factors that would adversely affect interpretations of time-lapse DAS observations.

Sensing whales, storms, ships and earthquakes using an Arctic fibre optic cable

Our oceans are critical to the health of our planet and its inhabitants. Increasing pressures on our marine environment are triggering an urgent need for continuous and comprehensive monitoring of the oceans and stressors, including anthropogenic activity. Current ocean observational systems are expensive and have limited temporal and spatial coverage. However, there exists a dense network of fibre-optic (FO) telecommunication cables, covering both deep ocean and coastal areas around the globe. FO cables have an untapped potential for advanced acoustic sensing that, with recent technological break-throughs, can now fill many gaps in quantitative ocean monitoring. Here we show for the first time that an advanced distributed acoustic sensing (DAS) interrogator can be used to capture a broad range of acoustic phenomena with unprecedented signal-to-noise ratios and distances. We have detected, tracked, and identified whales, storms, ships, and earthquakes. We live-streamed 250 TB of DAS data from Svalbard to mid-Norway via Uninett's research network over 44 days; a first step towards real-time processing and distribution. Our findings demonstrate the potential for a global Earth-Ocean-Atmosphere-Space DAS monitoring network with multiple applications, e.g. marine mammal forecasting combined with ship tracking, to avoid ship strikes. By including automated processing and fusion with other remote-sensing data (automated identification systems, satellites, etc.), a low-cost ubiquitous real-time monitoring network with vastly improved coverage and resolution is within reach. We anticipate that this is a game-changer in establishing a global observatory for Ocean-Earth sciences that will mitigate current spatial sampling gaps. Our pilot test confirms the viability of this 'cloud-observatory' concept.

Distributed vibration sensor with a lasing phase-sensitive OTDR

The authors experimentally demonstrate the operation of a lasing phase-sensitive optical time-domain reflectometer (Φ-OTDR) based on random feedback from a sensing fiber. Here, the full output of the laser provides the sensing signal, in contrast to the small backscattered signal measured in a conventional OTDR. In this proof-of-principle demonstration, the laser operates as a distributed vibration sensor with signal-to-noise ratio of 23-dB and 1.37-m spatial resolution.

High-precision distributed detection of rail defects by tracking the acoustic propagation waves

Nowadays, early defect detection plays a significant role for the railway safety warning. However, the existing methods cannot satisfy the requirements of real-time and high-precision detection. Here, a high-precision, distributed and on-line method for detecting rail defect is proposed and demonstrated. When a train goes through defects, the instantaneous elastic waves will be excited by the wheel-rail interaction, which will further propagate along railway tracks bidirectionally. Through mounting the backscattering enhanced optical fiber on the railway as sensors, the fiber optic distributed acoustic sensing system can record the propagation trace precisely. Further, the acoustic propagation fitting method is applied onto the propagation data to detect and locate defects along the long-distance railway. Especially, the dual-frequency joint-processing algorithm is proposed to improve the location accuracy. The field test proves that multiple defects along the railway can be successfully identified and located with a standard deviation of 0.314m. To the best of our knowledge, this work is the first report of distributed rail defect detection, which will bring a breakthrough for high-precision structural damage detection in the infrastructures such as the railway, pipeline and tunnel.

Distributed Acoustic Sensing for Monitoring Linear Infrastructures: Current Status and Trends

Linear infrastructures, such as railways, tunnels, and pipelines, play essential roles in economic and social development worldwide. However, under the influence of geohazards, earthquakes, and human activities, linear infrastructures face the potential risk of damage and may not function properly. Current monitoring systems for linear infrastructures are mainly based on non-contact detection (InSAR, UAV, GNSS, etc.) and geotechnical instrumentation (extensometers, inclinometers, tiltmeters, piezometers, etc.) techniques. Regarding monitoring sensitivity, frequency, and coverage, most of these methods have some shortcomings, which make it difficult to perform the accurate, real-time, and comprehensive monitoring of linear infrastructures. Distributed acoustic sensing (DAS) is an emerging sensing technology that has rapidly developed in recent years. Due to its unique advantages in long-distance, high-density, and real-time monitoring, DAS arrays have shown broad application prospects in many fields, such as oil and gas exploration, seismic observation, and subsurface imaging. In the field of linear infrastructure monitoring, DAS has gradually attracted the attention of researchers and practitioners. In this paper, recent research and the development activities of applying DAS to monitor different types of linear infrastructures are critically reviewed. The sensing principles are briefly introduced, as well as the main features. This is followed by a summary of recent case studies and some critical problems associated with the implementation of DAS monitoring systems in the field. Finally, the challenges and future trends of this research area are presented.

Indoor optical fiber eavesdropping approach and its avoidance

The optical fiber network has become a worldwide infrastructure. In addition to the basic functions in telecommunication, its sensing ability has attracted more and more attention. In this paper, we discuss the risk of household fiber being used for eavesdropping and demonstrate its performance in the lab. Using a 3-meter tail fiber in front of the household optical modem, voices of normal human speech can be eavesdropped by a laser interferometer and recovered 1.1 km away. The detection distance limit and system noise are analyzed quantitatively. We also give some practical ways to prevent eavesdropping through household fiber.

Rayleigh-Based Distributed Optical Fiber Sensing

Distributed optical fiber sensing is a unique technology that offers unprecedented advantages and performance, especially in those experimental fields where requirements such as high spatial resolution, the large spatial extension of the monitored area, and the harshness of the environment limit the applicability of standard sensors. In this paper, we focus on one of the scattering mechanisms, which take place in fibers, upon which distributed sensing may rely, i.e., the Rayleigh scattering. One of the main advantages of Rayleigh scattering is its higher efficiency, which leads to higher SNR in the measurement; this enables measurements on long ranges, higher spatial resolution, and, most importantly, relatively high measurement rates. The first part of the paper describes a comprehensive theoretical model of Rayleigh scattering, accounting for both multimode propagation and double scattering. The second part reviews the main application of this class of sensors.

Data Reduction in Phase-Sensitive OTDR with Ultra-Low Sampling Resolution and Undersampling Techniques

Data storage is a problem that cannot be ignored in the long-term monitoring of a phase-sensitive optical time-domain reflectometry (Φ-OTDR) system. In this paper, we proposed a data-reduction approach for heterodyne Φ-OTDR using an ultra-low sampling resolution and undersampling techniques. The operation principles were demonstrated and experiments with different sensing configurations were carried out to verify the proposed method. The results showed that the vibration signal could be accurately reconstructed from the undersampled 1-bit data. A space saving ratio of 98.75% was achieved by converting 128 MB of data (corresponding to 268.44 ms of sensing time) to 1.6 MB. The proposed method led to a potentially new data-reduction approach for heterodyne Φ-OTDR, which also provided economical guidance for the selection of the data-acquisition device.

On-line status monitoring and surrounding environment perception of an underwater cable based on the phase-locked Φ-OTDR sensing system

A newly designed phase-locked (PL) Φ-OTDR system was proposed and instrumented. Field tests of water impact, anchor damage towing and tide diagnosing were carried out in a natural freshwater lake as well as the East China Sea. Personnel movement trajectory monitoring and ship flow monitoring were carried out by a buried cable along the floodplain of the Yangtze River. It proved that the proposed system can monitor the real-time status and sense the surrounding environment of existing underwater communication cables, which could be helpful for the maintenance of the cable itself as well as underwater information collection.

Epicenter localization using forward-transmission laser interferometry

Widely distributed optical fibers, together with phase-sensitive laser interferometry, can expand seismic detection methods and have great potential for epicenter localization. In this paper, we propose an integral response method based on a forward transmission scheme. It uses spectrum analysis and parameter fitting to localize the epicenter. With the given shape of the fiber ring, the integral phase changes of light propagating in the forward and reverse directions can be used to determine the direction, depth, distance of the epicenter, and seismic wave speed. For the noisy case with SNR = 20 dB, the simulation results show ultrahigh precision when epicenter distance is 200 km: the error of the orientation angle is ∼0.003°±0.002°, the error of the P-wave speed is ∼0.9 ± 1.2 m/s, the error of the epicenter depth is ∼9.5 ± 400 m, and the error of the epicenter distance is ∼200 ± 760 m.

Quantifying the Surface Strain Field Induced by Active Sources with Distributed Acoustic Sensing: Theory and Practice

Quantitative dynamic strain measurements of the ground would be useful for engineering scale problems such as monitoring for natural hazards, soil-structure interaction studies, and non-invasive site investigation using full waveform inversion (FWI). Distributed acoustic sensing (DAS), a promising technology for these purposes, needs to be better understood in terms of its directional sensitivity, spatial position, and amplitude for application to engineering-scale problems. This study investigates whether the physical measurements made using DAS are consistent with the theoretical transfer function, reception patterns, and experimental measurements of ground strain made by geophones. Results show that DAS and geophone measurements are consistent in both phase and amplitude for broadband (10 s of Hz), high amplitude (10 s of microstrain), and complex wavefields originating from different positions around the array when: (1) the DAS channels and geophone locations are properly aligned, (2) the DAS cable provides good deformation coupling to the internal optical fiber, (3) the cable is coupled to the ground through direct burial and compaction, and (4) laser frequency drift is mitigated in the DAS measurements. The transfer function of DAS arrays is presented considering the gauge length, pulse shape, and cable design. The theoretical relationship between DAS-measured and pointwise strain for vertical and horizontal active sources is introduced using 3D elastic finite-difference simulations. The implications of using DAS strain measurements are discussed including directionality and magnitude differences between the actual and DAS-measured strain fields. Estimating measurement quality based on the wavelength-to-gauge length ratio for field data is demonstrated. A method for spatially aligning the DAS channels with the geophone locations at tolerances less than the spatial resolution of a DAS system is proposed.

Distributed acoustic sensing for active offshore shear wave profiling

The long-term sustainability of the offshore wind industry requires the development of appropriate investigative methods to enable less conservative and more cost-effective geotechnical engineering design. Here we describe the novel use of distributed acoustic sensing (DAS) as part of an integrated approach for the geophysical and geotechnical assessment of the shallow subsurface for offshore construction. DAS was used to acquire active Scholte-wave seismic data at several locations in the vicinity of a planned windfarm development near Dundalk Bay, Irish Sea. Complimentary additional datasets include high-resolution sparker seismic reflection, cone penetration test (CPT) data and gravity coring. In terms of fibre optic cable selection, a CST armoured cable provided a reasonable compromise between performance and reliability in the offshore environment. Also, when used as a seismic source, a gravity corer enabled the fundamental mode Scholte-wave to be better resolved than an airgun, and may be more suitable in environmentally sensitive areas. Overall, the DAS approach was found to be effective at rapidly determining shear wave velocity profiles in areas of differing geological context, with metre scale spatial sampling, over multi-kilometre scale distances. The application of this approach has the potential to considerably reduce design uncertainty and ultimately reduce levelised costs of offshore wind power generation.

Generation of high performance optical chirped pulse for distributed strain sensing application with high strain accuracy and larger measurement range

A photonic approach for generating low frequency drifting noise, arbitrary and large frequency chirping rate (FCR) optical pulses based on the Kerr effect in the nonlinear optical fiber is theoretically analyzed and experimentally demonstrated. Due to the Kerr effect-induced sinusoidal phase modulation in the nonlinear fiber, high order Kerr pulse with a large chirping rate is generated. In the concept-proof experiments, the FCR of the m^th Kerr pulse has been significantly improved by a factor of 2m+1. In addition, dynamic strain measurement along with a random fiber grating array (RFGA) sensor by using different order Kerr pulse is carried out for demonstrating a large strain measurement range with lower uncertainty sensing capability. Benefiting from the use of a single laser source and large FCR Kerr pulse, the system exhibits a 3.9 µɛ static strain measurable range, 0.24 µɛ measurement uncertainty by using -4^th order Kerr pulse that has an FCR up to 0.8 GHz/ns. Note that the FCR of the chirped pulse could be further enhanced by using larger FCR chirped pulse seed or choosing higher order Kerr pulses.

Polarization fading suppression in distributed interferometric sensing by matched interference between polarization-switched pulses

A polarization fading suppression technique is proposed for distributed interferometric sensing systems, based on matched interference between polarization switched pulses. For each individual sensor, two sets of interferometric outputs are obtained, one corresponding to the interference between two pulses with initially parallel polarization, the other corresponding to that between two pulses with initially orthogonal polarizations. As such, at least one output presents visibility no less than 2/2. By selecting the one with higher visibility for demodulation, the influence of polarization fading can be suppressed significantly, leading to distributed acoustic sensing with notably improved robustness and reliability.

Optical interferometry-based array of seafloor environmental sensors using a transoceanic submarine cable

Optical fiber-based sensing technology can drastically improve Earth observations by enabling the use of existing submarine communication cables as seafloor sensors. Previous interferometric and polarization-based techniques demonstrated environmental sensing over cable lengths up to 10,500 kilometers. However, measurements were limited to the integrated changes over the entire length of the cable. We demonstrate the detection of earthquakes and ocean signals on individual spans between repeaters of a 5860-kilometer-long transatlantic cable rather than the whole cable. By applying this technique to the existing undersea communication cables, which have a repeater-to-repeater span length of 45 to 90 kilometers, the largely unmonitored ocean floor could be instrumented with thousands of permanent real-time environmental sensors without changes to the underwater infrastructure.

Application of Intensity-Based Coherent Optical Time Domain Reflectometry to Bridge Monitoring

Although distributed fiber sensing techniques have been widely used in structural health monitoring, the measurement results of bridge monitoring, particularly under destructive testing, have rarely been reported. To the best of our knowledge, this paper is the first report of distributed vibration measurement results, which we obtained during a three-day destructive test on an abolished bridge. A coherent optical time domain reflectometry (COTDR) was used to acquire the vibration information while the bridge was being sawed. The obtained signal was analyzed in time and frequency domain. Some characteristics of the sawing-induced vibration were retrieved by the short-time Fourier transform; the vibration exhibited several high frequency components within the measured range up to 20 kHz and all the components appeared in the same time slot. Some unexpected signals were also detected. Thorough analysis showed that they are quite different from the sawing-induced vibration and are believed to originate from internal damage to the bridge (probably the occurrence of cracks).

Scientific Applications of Distributed Acoustic Sensing: State-of-the-Art Review and Perspective

This work presents a detailed review of the development of distributed acoustic sensors (DAS) and their newest scientific applications. It covers most areas of human activities, such as the engineering, material, and humanitarian sciences, geophysics, culture, biology, and applied mechanics. It also provides the theoretical basis for most well-known DAS techniques and unveils the features that characterize each particular group of applications. After providing a summary of research achievements, the paper develops an initial perspective of the future work and determines the most promising DAS technologies that should be improved.