Brillouin Optical Time Domain Reflectometry Research Articles

Improving BFS measurement accuracy of BOTDR based on Cauchy proximal splitting

A novel approach based on the Cauchy proximal splitting (CPS) algorithm is proposed to improve Brillouin frequency shift (BFS) measurement accuracy in Brillouin optical time domain reflectometry system. The CPS algorithm utilizes proximal splitting to handle the data and the penalty function based on Cauchy distribution to accurately estimate the target signal to promote sparsity, achieving significant improvement in signal-to-noise ratio (SNR). Experimental results confirm that with a SNR increase of 12.7 dB, an increase in BFS measurement accuracy from 4.78 MHz to 0.43 MHz is achieved over a 10.3 km sensing fiber. The denoising effects of the CPS, wavelet denoising (WD) and non-local mean (NLM) algorithms are further compared, demonstrating that the CPS algorithm has the lowest root mean square error (0.43 MHz) and no deterioration in spatial resolution rather than the WD and NLM algorithms does.

Fast Feature Extraction Method for Brillouin Scattering Spectrum of OPGW Optical Cable Based on BOTDR.

Brillouin optical time domain reflectometry (BOTDR) detects fiber temperature and strain data and represents one of the most critical ways of identifying abnormal conditions such as ice coverage and lightning strikes on optical fiber composite overhead ground wire (OPGW) cable. Existing BOTDR extracts brillouin frequency shift (BFS) features with cumulative averaging and curve fitting. BFS feature extraction is slow for long-distance measurements, making realizing real-time measurements on fiber optic cables challenging. We propose a fast feature extraction method for block matching and 3D filtering (BM3D) + Sobel brillouin scattering spectroscopy (BGS). BM3D takes the advantage of non-local means (NLM) and wavelet denoising (WD) and utilizes the spatial-domain non-local principle to enhance the denoising in the transform domain. The global filtering capability of BM3D is utilized to filter out the low cumulative average BGS noise and the BFS feature extraction is completed using Sobel edge detection. Simulation verifies the feasibility of the algorithm, and the proposed method is embedded in BOTDR to measure 30 km of actual OPGW line. The experimental results show that under the same conditions, the processing time of this method is reduced by 37 times compared to that with the 50,000-time cumulative averaging + levenberg marquardt (LM) algorithm without severe distortion of the reference resolution. The method improves the sensor demodulation speed by using image processing technology without changing the existing hardware equipment, which is expected to be widely used in the new generation of BOTDR.

Enhancing the Temperature-Measurement Efficiency in the Brillouin Optical Time-Domain Reflectometry (BOTDR) Fiber Sensor with the K-nearest Neighbor (K-NN) Algorithm

Enhancing the Temperature-Measurement Efficiency in the Brillouin Optical Time-Domain Reflectometry (BOTDR) Fiber Sensor with the K-nearest Neighbor (K-NN) Algorithm

Structure optimization and a detailed characteristic analysis for distributed Brillouin laser sensors

Distributed Brillouin laser sensor (DBLS) has shown its potential in terms of high signal-to-noise ratio (SNR) temperature/strain sensing without frequency sweeping. However, the discontinuous lasing in previous reports leads to limited resolution points and longer measurement time. In this letter, a structure optimization was proposed for DBLS to realize the continuous lasing and fully distributed sensing. Furthermore, a comprehensive experimental investigation on the sensing influence of key parameters, including net gain of lasing loop, peak power of pump pulse, and tolerance to the mismatch between pump pulse period and roundtrip time, has been explored detailly. The underlined physical mechanisms were also clarified experimentally. Compared with traditional Brillouin optical time-domain reflectometry (BOTDR), the substantially reduced standard deviation (STD) for distributed temperature sensing was demonstrated under the same averaging times. Related study can provide a new insight and design guideline for DBLS.

Smart textile embedded with distributed fiber optic sensors for railway bridge long term monitoring

The Structural Health Monitoring (SHM) of large civil infrastructures has become a priority due to economic advantages and early detection of structural failure. Distributed Fiber Optics (DFO) sensors are becoming widely used for SHM due to their immunity to Electromagnetic interference and the ability to collect multiple data points from a single fiber cable. However, its reliability for a long monitoring period is still an area of interest. This paper studied the long-term performance of DFO embedded into textiles for faster installation procedures. The aim was to understand if the textile distributed fiber sensor experience any signal degradation after multiple weather seasons. To perform this investigation a railway bridge was used as a case study. The data was collected using Brillouin Optical Time Domain Reflectometry (BOTDR) and Brillouin Optical Time Domain Amplification (BOTDA). Additionally, a temperature compensation technique was investigated to remove the cross-relation between temperature and strain. The final results show the sensor’s effectiveness for long-term monitoring, where the data quality remained constant with an average standard deviation of 0.455 for the BOTDR and 0.208 for the BOTDA approaches.

Towards single-photon Brillouin optical time domain reflectometry.

We investigate a novel distributed Brillouin optical time domain reflectometer (BOTDR) using standard telecommunication fibers based on single-photon avalanche diodes (SPADs) in gated mode, ν -BOTDR, with a range of 120 km and 10 m spatial resolution. We experimentally demonstrate the ability to perform a distributed temperature measurement, by detecting a hot spot at 100 km. Instead of using a frequency scan like conventional BOTDR, we use a frequency discriminator based on the slope of a fiber Bragg grating (FBG) to convert the count rate of the SPAD into a frequency shift. A procedure to take into account the FBG drift during the acquisition and perform sensitive and reliable distributed measurements is described. We also present the possibility to differentiate strain and temperature.

Detecting strain with a fiber optic cable on the seafloor offshore Mount Etna, Southern Italy

Oceans cover more than 70 percent of the Earth's surface making it difficult and costly to deploy modern seismological instruments here. The rapidly expanding global network of submarine telecom cables offers tremendous possibilities for seismological monitoring using laser light. Recent pioneer studies have demonstrated earthquake detection using lasers in onland and submarine fiber optic cables. However, permanent strain at the seafloor has never before been measured directly as it happens. With this aim, we deployed a dedicated 6-km-long fiber optic strain cable, offshore Catania Sicily, in 2000 m water depth, and connected it to a 29-km long electro-optical cable for science use. We report here that deformation of the cable equivalent to a total elongation of 2.5 cm was observed over a 21-month period (from Oct. 2020 to Jul. 2022). Brillouin laser reflectometry observations over the first 10 months indicate significant strain (+25 to +40 microstrain) at two locations where the cable crosses an active strike-slip fault on the seafloor, with most of the change occurring between 19 and 21 Nov. 2020. The cause of the strain could be fault slip or seabottom currents. During the following 11 months, the strain amplitude increased to +45 to +55 microstrain, affecting a longer portion of the cable up to 500 m to either side of the first fault crossing. A sandbag experiment performed on the distal portion of the cable (3.2–6.0 km) starting Sept. 2021 demonstrates how the fiber optic cable deforms in response to an applied load and how the deformation signal partially dissipates over time due to the elastic properties of the cable. These preliminary results are highly encouraging for the use of BOTDR (Brillouin Optical Time Domain Reflectometry) laser reflectometry as a technique to detect strain at the seafloor in near real time and to monitor the structural health of submarine cables.

Dual-parameter fiber sensor based on mode-division demultiplexing BOTDR system

We present and experimentally validate a neoteric and cost-effective dual-parameter distributed fiber sensor based on a Brillouin optical time-domain reflectometry in a general four-mode graded-index few-mode fiber. The spontaneous Brillouin scattering signals of different modes in the sensing fiber can be obtained simultaneously by a low-loss mode selective photonic lantern, on account of the difference of mode refractive indexes of different modes. By characterizing and evaluating the Brillouin scattering spectrum widths and the Brillouin frequency shift to temperature and strain sensitivities of different modes, the performance of the dual-parameter distributed sensor can be optimized. The proposed sensor achieves reliable differentiation of temperature and strain on a 1 km general four-mode graded-index few-mode fiber, with the temperature and strain accuracy of 1.6 °C and 39.2 με, respectively.

Strain Monitoring of Overhead Transmission Line Based on Brillouin Scattering

The change in the optical fiber state and the status of transmission line often leads to the change of strain in its composite optical fiber. This paper attempts to use a commercial BOTDR (Brillouin optical time-domain reflectometry) to monitor the strain of optical fiber composited in transmission line. The Brillouin spectra of typical optical fiber used in the transmission line are measured by a commercial BOTDR at room temperature, the spectra are fitted and the key parameters are calculated, and then the strain along whole optical fiber is obtained by demodulation. The results show that BOTDR can effectively monitor the optical fiber strain, and the mean standard deviation of strain measured for multiple measurements under the same condition is only about 8 με, which can stastify the requirements of practical cases. The work of this paper lays a foundation for the strain measurement of transmission line.

Fast and Accurate Brillouin Optical Time-Domain Sensing by Sparse Frequency Sampling and ANN-Based Recover Method

We propose a novel sparse frequency sampling and Brillouin scattering spectrum (BSS) recover method to greatly reduce the acquisition time of the frequency-sweep based Brillouin optical time domain sensor (BOTDS) without increasing hardware complexity. In the proposed method, the acquired BSSs only contain a few frequency points and thus show low resolution due to the sparse frequency sampling strategy. Then an artificial neural network (ANN) is used to accurately recover the BSSs with sparse frequency sampling to that with normal frequency sampling, and thus achieve fast and accurate temperature/strain measurement. In a proof-of-concept experiment, we measured the BSS of a 3 km sensing fiber and achieved 3 m spatial resolution by using a Brillouin optical time domain reflectometry (BOTDR) sensor. Through sparse frequency sampling, the data acquisition time is 5.5% with respect to that of the normal sampling. When the average (AVG) times of BSS is higher than 1000, the temperature measurement uncertainty is 0.2 °C.

Fiber optic monitoring of an anti-slide pile in a retrogressive landslide

Anti-slide piles are one of the most important reinforcement structures against landslides, and evaluating the working conditions is of great significance for landslide mitigation. The widely adopted analytical methods of pile internal forces include cantilever beam method and elastic foundation beam method. However, due to many assumptions involved in calculation, the analytical models cannot be fully applicable to complex site situations, e.g. landslides with multi-sliding surfaces and pile-soil interface separation as discussed herein. In view of this, the combination of distributed fiber optic sensing (DFOS) and strain-internal force conversion methods was proposed to evaluate the working conditions of an anti-sliding pile in a typical retrogressive landslide in the Three Gorges reservoir area, China. Brillouin optical time domain reflectometry (BOTDR) was utilized to monitor the strain distribution along the pile. Next, by analyzing the relative deformation between the pile and its adjacent inclinometer, the pile-soil interface separation was profiled. Finally, the internal forces of the anti-slide pile were derived based on the strain-internal force conversion method. According to the ratio of calculated internal forces to the design values, the working conditions of the anti-slide pile could be evaluated. The results demonstrated that the proposed method could reveal the deformation pattern of the anti-slide pile system, and can quantitatively evaluate its working conditions.

Large dynamic strain measurement via slope-assisted Brillouin optical time domain reflectometry using a frequency equalizer.

In this Letter, a method for measuring large dynamic strain via slope-assisted Brillouin optical time domain reflectometry (SA-BOTDR) is proposed. A linear artificial slope created by a frequency equalizer is used instead of the traditional slope of the Brillouin gain spectrum (BGS) as the linear response region between the Brillouin frequency shift (BFS) and signal intensity. This method makes the strain measurement range independent of the bandwidth of the BGS. The large dynamic strain with a maximum value of 3108 µε and the spatial resolution of 5 m along the ∼1.94-km single-mode fiber (SMF) are obtained by means of the proposed technique. Meanwhile, a strong linear relationship is also established between the signal strength and strain at the vibration frequencies of 10.3 and 13.1 Hz. The maximum measured errors of vibration frequency are 0.5 Hz@10.3 Hz and 0.8 Hz@13.1 Hz.

OPGW positioning and early warning method based on a Brillouin distributed optical fiber sensor and machine learning.

A method of optical fiber composite overhead ground wire (OPGW) positioning based on a Brillouin distributed optical fiber sensor and machine learning is proposed. A distributed Brillouin optical time-domain reflectometry (BOTDR) and Brillouin optical time-domain analyzer (BOTDA) are designed, where the ranges of BOTDR and the BOTDA are 110km and 125km, respectively. An unsupervised machine learning method density-based spatial clustering of applications with noise (DBSCAN) is proposed to automatically identify the splicing point based on the Brillouin frequency shift (BFS) difference of adjacent sections. An adaptive parameter selection method based on k-distance is adapted to overcome the parameter sensitivity. The validity of the proposed DBSCAN algorithm is greater than 96%, which is evaluated by three commonly external validation indices with five typical BFS curves. According to the clustering results of different fiber cores and the tower schedule of the OPGW, the connecting towers are distinguished, which is proved as a 100% recognition rate. According to the identification results of different fiber cores of both the OPGW cables and tower schedule, the connecting towers can be distinguished, and the distributed strain information is extracted directly from the BFS to strain. The abnormal region is positioned and warned according to the distributed strain measurements. The method proposed herein significantly improves the efficiency of fault positioning and early warning, which means a higher operational reliability of the OPGW cables.

Denoising of BOTDR Dynamic Strain Measurement Using Convolutional Neural Networks.

The Brillouin optical time domain reflectometry (BOTDR) system measures the distributed strain and temperature information along the optic fibre by detecting the Brillouin gain spectra (BGS) and finding the Brillouin frequency shift profiles. By introducing small gain stimulated Brillouin scattering (SBS), dynamic measurement using BOTDR can be realized, but the performance is limited due to the noise of the detected information. An image denoising method using the convolutional neural network (CNN) is applied to the derived Brillouin gain spectrum images to enhance the performance of the Brillouin frequency shift detection and the strain vibration measurement of the BOTDR system. By reducing the noise of the BGS images along the length of the fibre under test with different network depths and epoch numbers, smaller frequency uncertainties are obtained, and the sine-fitting R-squared values of the detected strain vibration profiles are also higher. The Brillouin frequency uncertainty is improved by 24% and the sine-fitting R-squared value of the obtained strain vibration profile is enhanced to 0.739, with eight layers of total depth and 200 epochs.

Design a remote sensing of multi-BOTDR fiber optic sensors for fuel pipeline monitoring

The necessity for environmental protection has led to the development of different sensors for monitoring fuel pipelines to avoid explosion, leakage, and corrosion. Distributed optical fiber sensors-based Brillouin scattering have become progressively common because of their novel feature of simultaneously determining temperature, vibration, and strain. The stimulated Brillouin scattering (SBS) threshold power, sensing distance, single-mode fiber cable length, and sensing accuracy are serious parameters to the implementation of Brillouin optical time-domain reflectometry (BOTDR) sensor. In this study, remote sensing of multi-BOTDR fiber optic sensors for fuel pipeline monitoring is designed and presented. The results of simulations and theoretical explainations on suppressing fiber optic nonlinearity are analyzed. Results show that an SBS suppression via 16 dB is required to attain the maximum multi-remote sensing distance of up to 20 km for each network and a perfect frequency shift of 11 GHz. An open eye pattern corresponds to minimal signal distortion with a high Q-factor of 22 for the developed sensor. The highest sensing accuracy of 0.3318 %/K indicating power change (%) is observed from 290–300 K at 193.1 THz operating frequency.

Single-photon detector-based long-distance Brillouin optical time domain reflectometry

We present a long-range Brillouin optical time domain reflectometer (BOTDR) based on photon counting technology. We demonstrate experimentally the ability to perform a distributed temperature measurement, by detecting a hot spot in a thermal bath at 100 km, and the possibility to achieve measurement until 120 km with a spatial resolution of 10 m. We use the slope of a fiber Bragg grating (FBG) as a frequency discriminator, to convert count rate variation into a frequency shift. A performance study of our distributed sensor as a function of spatial resolution is also presented.

Hybrid Fiber Optic Cable for Strain Profiling and Crack Growth Measurement in Rock, Cement, and Brittle Installation Media.

Brillouin scattering-based distributed fiber optic sensing (DFOS) technologies such as Brillouin optical time domain reflectometry (BOTDR) and Brillouin optical time domain analysis (BOTDA) have broad applicability for the long term and real-time monitoring of large concrete structures, underground mine excavations, pit slopes, and deep subsurface wellbores. When installed in brittle media, however, the meter scale spatial resolution of the BOTDR/A technology prohibits the detection or measurement of highly localized deformations, such as those which form at or along cracks, faults, and other discontinuities. This work presents a novel hybrid fiber optic cable with the ability to self-anchor to any brittle installation media without the need for manual installation along fixed interval points. Laboratory scale testing demonstrates the ability of the hybrid fiber optic cable to measure strains across highly localized deformation zones in both tension and shear. In addition, results show the applicability of the developed technology for strain monitoring in high displacement environments. Linear relationships are proposed for use in estimating the displacement magnitude along discontinuities in brittle media from strain signals collected from the hybrid fiber optic cable. The hybrid fiber optic cable has broad potential applications, such as geomechanical monitoring in underground mines, surface pits, large civil infrastructure projects, and deep subsurface wellbores. The benefits of fiber optic sensing, such as the intrinsic safety of the sensors, the long sensing range, and real time capabilities make this a compelling technique for long term structural health monitoring (SHM) in a wide range of industrial and civil applications.

Fast and accurate Brillouin frequency shift extraction in Brillouin optical time domain reflectometry (BOTDR) distributed fiber sensor by using ensemble machine learning algorithm

To improve the Brillouin frequency shift (BFS) resolution measurement and processing time of the differential cross-spectrum Brillouin optical time domain reflectometry (DCS-BOTDR) fiber sensor, our team suggests employing the ensemble machine learning (EML) technique. Because it gave the best BFS resolution compared to the other TL cases, we used the BFS distribution data recorded by the pulse duration TL =14 ns case as ground truth to train the EML model in this work. After that, we tested the EML model for TL =4, 60, and 90 ns cases. We improved the BFS resolution for all TL situations by approximately 2.85 MHz, comparable to our resolution when TL was equal to 14 ns. This result demonstrates that the EML algorithm is reliable, efficient, and highly accurate in its predictive capabilities. Additionally, we have documented a rapid processing time of approximately one second. In addition, we have successfully demonstrated 20 cm spatial resolution measurement for TL =60 and 90 ns, which was not previously possible with the usual DCS-BOTDR signal processing method.

Comparison of Raman, Brillouin, and Rayleigh Distributed Temperature Measurements in High-Rate Wells

With the maturity of and demand for fiber-optic sensing technology growing steadily over the last few years across multiple basins, operators are seeking fiber-optic sensing solutions that address the technology challenges associated with the life-of-field monitoring of subsea developments. Single-ended distributed temperature sensing (DTS) measurements have been acquired for decades now, typically using Raman optical time-domain reflectometry (OTDR) on multimode fiber. However, for topside interrogation of subsea completions, Raman DTS performs poorly. This is due to the available optical power budget and the potential wavelength dependency of optical attenuation across multiple connectors and splices comprising the optical subsea infrastructure. Any wavelength-dependent attenuation as the signals pass through connectors, splices, and optical feedthrough systems will generate step changes in the measured Raman DTS temperature profile. Brillouin OTDR can provide a DTS alternative that overcomes these challenges and operates on single-mode fiber. Brillouin OTDR operates with a large dynamic range to measure a wavelength (frequency) shift of the Stokes/anti-Stokes components that is proportional to both strain and temperature. Since downhole cables are manufactured with optical fibers suspended in a gel and with appropriate extra fiber length (EFL), any fiber strain relaxes, and the Brillouin wavelength shift is an absolute temperature measurement. An additional alternative is also explored here. We typically associate coherent Rayleigh OTDR with distributed acoustic sensing (DAS) on single-mode fibers, but low frequencies also contain a relative temperature dependence. The low-pass filtering of DAS data can then be used as a form of Rayleigh DTS with appropriate data processing. In this paper, we report on a comparison of Raman, Brillouin, and Rayleigh DTS simultaneously acquired in the same high-rate producer and injector wells. We validate that, with appropriate cable design, Brillouin DTS can be simultaneously operated on the same single-mode fiber with DAS and can deliver absolute temperature measurements suitable for production analysis. We also use a laboratory experiment to show that Rayleigh DTS provides an accurate measure of temperature changes comparable in precision to a traditional thermocouple. We conclude with a discussion about the implementation of this DAS-DTS solution for sensing subsea completions.

Probe pulse design in Brillouin optical time‐domain reflectometry

Brillouin optical time-domain reflectometry (BOTDR) is a branch of distributed fibre-optic sensors, and it can measure the strain and the temperature information, localised by the return time of the probe pulse, along the fibre based on the spontaneous Brillouin scattering process. Parameters of the BOTDR system, including the spatial resolution, the signal-to-noise ratio, the measurement speed, and the sensing range, have a mutually restrictive relationship. In order to improve the performance of the BOTDR system, researchers have focussed on improving the design of the probe pulse, for example, transforming the shape, the sequence, and the spectral properties of the pulse. This study summarises the recent progress in the design of detection pulses in BOTDR systems, and comprehensively demonstrates the improvement effects of various pulse modulation formats on the system performance.