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In this paper, aiming at a large infrastructure structural health monitoring network, a quaternion wavelet transform (QWT) image denoising algorithm is proposed to process original data, and a depth feedforward neural network (FNN) is introduced to extract physical information from the denoised data. A Brillouin optical time domain analysis (BOTDA)-distributed sensor system is established, and a QWT denoising algorithm and a temperature extraction scheme using FNN are demonstrated. The results indicate that when the frequency interval is less than 4 MHz, the temperature error is kept within ±0.11 °C, but is ±0.15 °C at 6 MHz. It takes less than 17 s to extract the temperature distribution from the FNN. Moreover, input vectors for the Brillouin gain spectrum with a frequency interval of no more than 6 MHZ are unified into 200 input elements by linear interpolation. We hope that with the progress in technology and algorithm optimization, the FNN information extraction and QWT denoising technology will play an important role in distributed optical fiber sensor networks for real-time monitoring of large-scale infrastructure. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel method under convolutional neural network framework combined with a supervised variational autoencoder and an attention mechanism, named the Restoration and Extraction Convolutional Neural Network (RECNN), for the restoration and extraction of Incomplete Brillouin Gain Spectrum (IBGS). It is important to clarify that the IBGS discussed here does not encompass information around the Brillouin Frequency Shift (BFS). This omission complicates the task of reconstructing the original spectrum or determining the BFS value. The RECNN framework consists of two main components: Restoration Supervised Variational Autoencoder (RSVAE) with an attention module for IBGS restoration, and Residual Attention Convolutional Neural Network (RACNN) for BFS extraction. Different types of IBGS are discussed in detail. We define the K index to quantify the incompleteness of the IBGS and introduce the R-squared index to measure the restoration performance of RSVAE. Additionally, the Root Mean Square Error (RMSE) and uncertainty are used to evaluate the overall performance of RECNN. Both simulation and experimental results demonstrate that the R-squared index increases with increasing K and Signal-to-Noise Ratio (SNR), while both RMSE and uncertainty decrease with increasing K and SNR. In comparisons with various other methods including Linear Curve Fitting (LCF) and artificial neural networks, RECNN consistently outperforms them. Specifically, simulation results show that when K is 0.5 and SNR is 4 dB, the R-squared value for RSVAE reaches 0.82, significantly higher than the 0.31 achieved by LCF method. Experimental results indicate that for an SNR of 6.78 dB and K of 0.5, the RMSE and uncertainty of RECNN are 3.21 MHz and 2.68 MHz, respectively, representing reductions of 11.43 MHz and 11.17 MHz compared to LCF. It's noteworthy that the time consumption evaluation indicates that RECNN requires less than 7 ms to restore the complete BGS and obtain the BFS value. These results are consistently observed in both simulations and experimental studies, which bodes well for the future of extracting valuable latent information from outdated and corrupted data stored in databases of distributed fiber sensing applications. [ABSTRACT FROM AUTHOR]

• Poor real-time performance of Brillouin system during long-distance monitoring. • Changing the frequency sweep step size can affect accuracy and processing speed. • An increase in monitoring distance will lead to a decrease in signal-to-noise ratio. • The processing accuracy of temporal convolutional networks is less than 1 °C. • Temporal convolutional networks can handle data with a signal-to-noise ratio of 5 dB. The Brillouin optical time-domain sensing system has become a hot spot of research due to its ability to seamlessly monitor the temperature and strain variations in optical fibers along the line. Given its current limitations of low accuracy and inadequate real-time performance in long-distance monitoring, the Brillouin gain extraction temperature method based on temporal convolutional networks is proposed. On this basis, we established a Brillouin optical time-domain experimental system where comprehensive simulations and tests were conducted to assess the temperature extraction performance under different conditions. Besides, a comparison was made between the system and traditional methods like Lorentz fitting method and extreme learning machine method. The results have suggested that the temporal convolutional network exhibits remarkable measurement accuracy, even in scenarios with low signal-to-noise ratios and large sweep frequency steps. [ABSTRACT FROM AUTHOR]

Artificial neural networks (ANNs) can be used to replace the traditional methods in various fields, making signal processing more efficient and meeting the real-time processing requirements of the Internet of Things (IoT). Recently, as a special type of ANN, the feedforward neural network (FNN) has been used to replace the time-consuming Lorentzian curve fitting (LCF) method in Brillouin optical time-domain analysis (BOTDA) system to retrieve the Brillouin frequency shift (BFS), which could be used as the indicator in temperature/strain sensing and so on. However, the FNN needs to be re-trained if the generalization ability is not satisfactory, or the frequency scanning step is changing in the experiment. This is a cumbersome and inefficient process. In this paper, the FNN only needs to be trained once with the proposed method, and 150.62 km BOTDA is built to verify the performance of the trained FNN. The simulation and experimental results show that the proposed method is promising in BOTDA because of its high computational efficiency and wide adaptability.

In this paper, an assessment method of excavation disturbance effect is proposed by using distributed optical-fiber strain sensing technique. Model tests of trenchless construction under different parameter conditions are carried out in the laboratory. In the test, the excavation was simulated by using the deflate of pre-burying air bag, soil displacement is measured by settlement mark, at the same time, The soil strain of overburden layer is obtained based on Brillouin Optical Time-Domain Analysis (BOTDA). Through the analysis of the experimental data, the partition theory of excavation disturbance zone is proved and verified through test data. The correlation between ground settlement and soil strain distribution due to trenchless construction are compared and analyzed. The mechanical response of overlying pavement are further discussed. Research results indicate that soil strain of overburden layer is symmetrically distributed about the excavation surface, which is compressed near the centerline and tensioned on both sides due to the excavation disturbance impact. The width of excavation disturbance zone derived from the test data shows good accordance with the calculation results based on the partition theory, the maximum error is less than 10%. A certain consistency exists between the distribution law of strain curve and settlement trough. Due to the uneven distribution of support force caused by foundation settlement, the pavement model shows notable bending deflection after trenchless excavation, and the maximum increment ratio of support force exceed 50%. The combined impact of ground traffic load and excavation disturbance is considered to be more unfavorable to the safety of pavement structure. The conclusions can be suggestive and helpful to trenchless excavation control. [ABSTRACT FROM AUTHOR]

Brillouin optical time-domain analysis (BOTDA) that operates over a long sensing fiber is prone to be affected by the detrimental non-local effects (NLE); since NLE can distort Brillouin gain spectrum (BGS), therefore correctly retrieving Brillouin frequency shift (BFS) is very challenging. Recently, the basic artificial neural networks (B-ANN) has been demonstrated to retrieve BFS effectively, in the case that a distortion-free BGS can be obtained. However, in the more general cases with NLE, a neural network for retrieving BFS in BOTDA data has not been proposed. In this paper, firstly the physical origin of NLE is analyzed theoretically and experimentally in detail. Then a specific ANN (NLE-ANN) is proposed to deal with the BOTDA data affected by NLE for the first time. The experimental verifications show that with the cooperative implementation of NLE-ANN and B-ANN, the effective retrieval of BFS along the whole fiber can be achieved, even though the BGS has been affected by NLE. This work proposes a promising approach in traditional BOTDA, because the upper limit of probe power could be raised by artificial intelligence to boost the sensing performance. [ABSTRACT FROM AUTHOR]

Distributed optical fiber strain sensing significantly increases the number of sensing points compared with fiber Bragg grating sensor, which makes it an excellent candidate for shape sensing. Theoretical analysis indicates that the spatial resolution of strain measurement is crucial to the performance of shape sensing, so a shape sensor based on differential pulse-width-pair Brillouin optical time-domain analysis is proposed to improve the spatial resolution and shape sensing performance. The sensing fiber is attached on the both sides of a steel strip substrate, which enables the measurement of Brillouin frequency shifts (BFSs) of both the sides to suppress temperature crosstalk. In the experiment, first, the dependence of BFS variation on the curvature of the fiber is measured, the result of which agrees well with theory. Then the reconstruction of three shapes are demonstrated, the spatial resolution of which is 10 cm.

Optical fiber sensing (OFS) systems can be used to accurately measure temperature, strain, pressure, and other physical parameters by detecting the change in the field of lightwave. As they are used in more application areas, a new type of OFS with the ability of providing multi-dimensional, highly sensitive, ultra-fine, and real-time measurement is necessary. This is possible with the application of digital coherent optical technologies in the OFS systems. In this paper, we show that many aspects of OFS systems can be replaced or enhanced by digital coherent optical technologies. For example, digital optical frequency comb (DOFC) can replace the sweeping laser source, and the digital coherent optical receiver can replace the direct detection receiver to enable simultaneous detection of all the dimensions of lightwave. Based on these techniques, we present our research progresses on OFS with multi-dimensional, real-time, ultra-fine spectral analysis, and single-shot Brillouin optical time-domain analysis based DOFC for distributed OFS. We show that the OFS systems can be bought to a whole new level with the capabilities of real-time time–frequency analysis, ultra-fine spectral resolution, and ultra-low sensitivity. Opportunities and challenges of using digital coherent optical technologies in OFS systems are also discussed. [ABSTRACT FROM AUTHOR]

Distributed fiber sensing (DFS) can provide real-time signals and warnings. The entire length of fiber optic cable can act as a sensing element, but the accuracy is sometimes limited. On the other hand, point-to-point fiber sensing (PPFS) is usually implemented using one or more fiber Bragg gratings (FBGs) at specific positions along with the fiber for the monitoring of specific parameters (temperature, strain, pressure, and so on). However, the cost becomes expensive when the number of FBGs increases. A hybrid fiber sensing scheme is thus proposed, combining the advantages of DFS and PPFS. It is based on a Brillouin optical time-domain analysis (BOTDA) fiber system with additional FBGs embedded at certain positions where it is necessary to detect specific parameters. The hybrid fiber sensing system has the advantages of full sensing coverage at essential locations that need to be carefully monitored. In our work, the test results showed that the proposed system could achieve a sensing distance of 16 km with the single-mode fiber with a 2 m spatial resolution. For FBG parameter measurements, the temperature variation was 52 °C, from 25 °C to 77 °C, with a temperature sensitivity of 23 pm/°C, and the strain was from 0 to 400 µε, with a strain sensitivity of 0.975 pm/µε, respectively, using two FBGs.

This study proposes the use of heterodyne detection and wavelength scanning techniques to solve the problems of small signal and large noise in a Rayleigh Brillouin optical time-domain analysis (BOTDA) system and thereby improve the system performance. Based on an analysis of the Rayleigh BOTDA system, heterodyne detection is used to enhance the signal intensity and wavelength scanning is used to reduce the fading noise. Experimental results obtained using the proposed techniques show that the amplitude fluctuation and signal-to-noise ratio in a 50-m-long fiber near the fiber end with 17 wavelength scans-based averaging are, respectively, reduced by 0.91 dB and increased by 4.19 dB compared to those with a single wavelength. Furthermore, the Brillouin frequency shift in a 70-m-long fiber heated to 50°C and inserted at the center of the sensing fiber can be measured accurately with a maximum fluctuation of 0.19 MHz; this is equivalent to a temperature measurement accuracy of 0.19°C. These results indicate that the proposed techniques can realize high-accuracy measurement, and therefore, they show great potential in the field of long-distance and high-accuracy sensing. [ABSTRACT FROM AUTHOR]

To address the issues of high time consumption of frame synchronization involved in a scanning-free Brillouin optical time-domain analysis (SF-BOTDA) system, a fast frame synchronization algorithm based on incremental updating was proposed. In comparison to the standard frame synchronization algorithm, the proposed one significantly reduced the processing time required for the BOTDA system frame synchronization by about 98%. In addition, to further accelerate the real-time performance of frame synchronization, a field programmable gate array (FPGA) hardware implementation architecture based on parallel processing and pipelining mechanisms was also proposed. Compared with the software implementation, it further raised the processing speed by 13.41 times. The proposed approach could lay a foundation for the BOTDA system in the field with the associated high real-time requirements.

Distributed optical fiber strain sensing significantly increases the number of sensing points compared with fiber Bragg grating sensor, which makes it an excellent candidate for shape sensing. Theoretical analysis indicates that the spatial resolution of strain measurement is crucial to the performance of shape sensing, so a shape sensor based on differential pulse-width-pair Brillouin optical time-domain analysis is proposed to improve the spatial resolution and shape sensing performance. The sensing fiber is attached on the both sides of a steel strip substrate, which enables the measurement of Brillouin frequency shifts (BFSs) of both the sides to suppress temperature crosstalk. In the experiment, first, the dependence of BFS variation on the curvature of the fiber is measured, the result of which agrees well with theory. Then the reconstruction of three shapes are demonstrated, the spatial resolution of which is 10 cm. [ABSTRACT FROM AUTHOR]

Brillouin optical time-domain analysis (BOTDA) sensors have great potential to provide distributed measurements of temperature and strain over large structures with high spatial resolution and measurement precision. However, their performance ultimately depends on the amount of probe and pump pulse power that can be injected into the sensing fiber, which determines the signal-to-noise ratio of the detected measurement signal. The probe wave power is constrained by the generation of noise induced by spontaneous Brillouin scattering and at lower power by the so-called non-local effects. In this work, we focus on the latter. We review the physical origins of non-local effects and analyze the performance impairments that they bring. In addition, we discuss the different methods that have been proposed to counteract these effects comparing their relative merits and ultimate performance. Particularly, we focus on a technique that we have devised to compensate non-local effects which is based on introducing an optical frequency modulation or dithering to the probe wave. This method is shown to provide a comprehensive solution to most of the impairments associated with non-local effects and also to enable some side benefits, such as amplification of the pump pulses to compensate the attenuation of the fiber. [ABSTRACT FROM AUTHOR]

• A method is proposed to monitor the convergence deformation of shield tunnels by distributed BOTDA sensors. • The additional settlement deformation induced by flattening effect is calculated with high-density strain data. • Multisection convergence deformation is calculated based on the spatial correlation of strain and convergence for shield tunnel using ANN. • Accuracy of convergence deformation is improved compared to the state-of-the-art. The convergence deformation of shield tunnels, which is induced by the combination of the local circumferential load and the flattening effect under longitudinal differential settlement, is difficult to comprehensively monitor with point sensing technology. To address this problem, a method for convergence monitoring considering the flattening effect in shield tunnels is proposed based on distributed Brillouin optical time-domain analysis (BOTDA) technology. First, the convergence deformation under sectional circumferential pressure is explored based on the conjugated beam method; second, the additional influence of the flattening effect, including extrusion and shear effects, on settlement is analyzed using the force method; third, considering the actual circumferential layout of the distributed optical fiber sensors, the multisection convergence is determined from the spatial correlations of the cross-sectional strain monitoring data by means of an artificial neural network (ANN); then, finally, using the time-series monitoring data, the trend of the convergence deformation can be predicted. In this study, both numerical simulation and practical application are carried out to validate the effectiveness of the proposed method, which is compared with the existing method without consideration of the flattening effect. The results indicate that the proposed method enables high accuracy and robustness in convergence monitoring, thus providing a referential basis for further tunnel operation and maintenance. [ABSTRACT FROM AUTHOR]

A method for monitoring the upheaval buckling of subsea buried pipelines by distributed optical fiber sensors is introduced. The proposed method originates from the fact that the bucked pipe has the deterministic patterns of the bending-induced and axial force--induced strains, which can be used to identify the pre- and post-buckling states of the pipe. The challenge for utilizing these features is that the distributed fiber optic sensor can only measure the compound strain created by both bending and axial compression. A monitoring scheme by placing three sensors with 2p=3 space around the circumference of the pipeline was proposed in this article. An approach was presented to extract the bending-induced and axial force--induced strains from the longitudinal strains measured by the distributed fiber optic sensors. The experimental programs were then designed to investigate the feasibility of the proposed method. It is demonstrated that the proposed method is possible to detect the occurrence of buckling in the pipe. However, further research is necessary in order to examine the efficiency of the proposed approach under the complex loading patterns at subsea levels. [ABSTRACT FROM AUTHOR]

Brillouin optical time-domain analysis (BOTDA) sensors have great potential to provide distributed measurements of temperature and strain over large structures with high spatial resolution and measurement precision. However, their performance ultimately depends on the amount of probe and pump pulse power that can be injected into the sensing fiber, which determines the signal-to-noise ratio of the detected measurement signal. The probe wave power is constrained by the generation of noise induced by spontaneous Brillouin scattering and at lower power by the so-called non-local effects. In this work, we focus on the latter. We review the physical origins of non-local effects and analyze the performance impairments that they bring. In addition, we discuss the different methods that have been proposed to counteract these effects comparing their relative merits and ultimate performance. Particularly, we focus on a technique that we have devised to compensate non-local effects which is based on introducing an optical frequency modulation or dithering to the probe wave. This method is shown to provide a comprehensive solution to most of the impairments associated with non-local effects and also to enable some side benefits, such as amplification of the pump pulses to compensate the attenuation of the fiber.

An optimized hybrid Raman/BOTDA optical fiber sensor based on cyclic Simplex pulse coding is proposed to overcome temperature and strain cross-sensitivity issues, allowing at the same time fast implementation of Brillouin optical time domain analysis with subsecond measurement times. By providing a real-time diagnostic system for safe operation, the proposed sensor can play a key role for in-service monitoring of large critical infrastructures. Experimental results demonstrate the capability of the proposed technique to effectively discriminate the Brillouin frequency shift contributions due to strain and temperature variations simultaneously applied to the same fiber section along 10 km of standard single mode optical fiber, with 1-m spatial resolution and a worst-case strain resolution value of 62 με. The proposed scheme uses a single narrowband laser source and one sensing fiber only. [ABSTRACT FROM PUBLISHER]

We demonstrate a high-spatial-resolution fast Brillouin optical time-domain analysis scheme based on frequency agility and differential double-pulse for distributed dynamic measurement. The frequency-agility probe wave is obtained from the second-order sideband of modulated light by using frequency-agility microwave signal from a wideband arbitrary waveform generator. The differential double-pulse technique is proposed to improve the spatial resolution while keeping the capability of dynamic measurement. In experiment, a spatial resolution of 20 cm is achieved by using a 52/50 ns differential double-pulse, and the distributed vibration measurement is demonstrated over a 50-m Panda fiber with a maximum vibration frequency of up to 50 Hz. With only five averages, the standard deviation of the strain accuracy is of 14 μV. [ABSTRACT FROM AUTHOR]

Raman-assistance (RA) has been identified as a promising technique to extend the measurement range of Brillouin optical time-domain analysis (BOTDA)-based distributed sensors. Unfortunately, Raman amplification introduces a great amount of relative intensity noise (RIN) to the detected low-frequency probe wave. This RIN transfer problem has been widely identified as a major limitation in RA-BOTDA. In vector BOTDA (VBOTDA), the detected signal is transferred to a high-frequency carrier where the Raman RIN transfer turns out to be much less harmful. In addition, a VBOTDA can also provide information about the phase-shift induced by the local stimulated Brillouin scattering gain curve, paving the way for dynamic measurements. In this letter, we demonstrate, for the first time to our knowledge, the RA in a VBOTDA obtaining gain and phase measurements. Our results show a significant reduction of the RIN transfer effect in RA-VBOTDA compared with standard RA-BOTDA, making this type of scheme particularly interesting for long-range and dynamic distributed sensing. [ABSTRACT FROM PUBLISHER]

Raman assistance in distributed sensors based on Brillouin optical time-domain analysis can significantly extend the measurement distance. In this paper, we have developed a 2 m resolution long-range Brillouin distributed sensor that reaches 100 km using first-order Raman assistance. The estimated uncertainty in temperature discrimination is 1.2°C, even for the position of worst contrast. The parameters used in the experiment are supported by a simple analytical model of the required values, considering the main limitations of the setup. [ABSTRACT FROM PUBLISHER]

This paper reports on a new mechanism to decrease the number of averages and, consequently, the measurement time of Brillouin optical time-domain analysis (BOTDA) sensors using wavelet shrinkage techniques. Two different wavelet shrinkage techniques, VisuShrink and SureShrink, are applied to denoise signals acquired from measurements in BOTDA sensors. The conventional method to denoise signals in BOTDA sensors is ensemble averaging. Ensemble averaging is a time consuming technique, as it requires many acquisitions of signals to provide an acceptable SNR. To reduce the number of acquisitions, the setup of the BOTDA sensor is modified to denoise acquired signals using VisuShrink or SureShrink before applying ensemble averaging. Experimental results show a significant reduction in the number of averages required to provide an accurate measurement, and consequently, a substantial saving in the measurement time of the sensor. It has been shown that the combination of ensemble averaging with VisuShrink or SureShrink reduces the measurement time of the sensor up to 90%. This reduction in the measurement time enables the implementation of dynamic and fast measurements with BODTA sensors and opens opportunities to target a new range of applications. [ABSTRACT FROM PUBLISHER]

• Discussing the condition required for converting the strain into cross-sectional curvature. • Proposing a discriminative method of converting the strains into cross-sectional curvature. • Detecting the damage of tunnel using strain data from BOTDA sensors. Fully distributed Brillouin-scattering-based optical sensors—e.g., Brillouin optical time-domain analysis (BOTDA) sensors—appear to be promising supplementary tools for the SHM of actual tunnels. As far as we know, there is little research on detecting the damage of tunnels by using the strain continuous monitoring data obtained from BOTDA sensors. To address this issue, a method based on high-density cross-sectional curvature is proposed for the damage detection of operating tunnel. First, considering the long-distance and large-scale characteristics of actual tunnels, the strain is not sufficiently sensitive to structural damage; thus, the structural strain is converted into the cross-sectional curvature of the tunnel in order to improve this sensitivity. The condition required for converting the strain at the measured points into corresponding measurements of the cross-sectional curvature of the tunnel is discussed, and on this basis, a discriminative approach to the abovementioned conversion is presented. Second, a damage detection index based on high-density cross-sectional curvature is established, and combined with the novel detection approach, the proposed index is implemented to detect the damage of the tunnel. Finally, numerical examples are presented to analyze and discuss the noise resistance performance and structural damage sensitivity of the proposed method. Moreover, the effectiveness of the proposed method is demonstrated using strain monitoring data obtained from an actual tunnel with a box-type structure. [ABSTRACT FROM AUTHOR]

Distributed fiber sensing (DFS) can provide real-time signals and warnings. The entire length of fiber optic cable can act as a sensing element, but the accuracy is sometimes limited. On the other hand, point-to-point fiber sensing (PPFS) is usually implemented using one or more fiber Bragg gratings (FBGs) at specific positions along with the fiber for the monitoring of specific parameters (temperature, strain, pressure, and so on). However, the cost becomes expensive when the number of FBGs increases. A hybrid fiber sensing scheme is thus proposed, combining the advantages of DFS and PPFS. It is based on a Brillouin optical time-domain analysis (BOTDA) fiber system with additional FBGs embedded at certain positions where it is necessary to detect specific parameters. The hybrid fiber sensing system has the advantages of full sensing coverage at essential locations that need to be carefully monitored. In our work, the test results showed that the proposed system could achieve a sensing distance of 16 km with the single-mode fiber with a 2 m spatial resolution. For FBG parameter measurements, the temperature variation was 52 °C, from 25 °C to 77 °C, with a temperature sensitivity of 23 pm/°C, and the strain was from 0 to 400 µε, with a strain sensitivity of 0.975 pm/µε, respectively, using two FBGs. [ABSTRACT FROM AUTHOR]

In this paper, Gaussian smoothing (GS), non-local means (NLM), and Quaternion Wavelet Transform (QWT) have been described in detail. Furthermore, a Brillouin optical time domain analysis (BOTDA) experimental system was built to verify the denoising algorithms. The principal and experimental analyses show that the QWT algorithm is a more efficient image denoising method. The results indicate that the GS algorithm can obtain the highest signal-to-noise ratio (SNR), frequency uncertainty, and Brillouin frequency shift (BFS) accuracy, and can be executed in an imperceptible time, but the GS algorithm has the lowest spatial resolution. After being denoised by using NLM algorithm, although SNR, frequency uncertainty, BFS accuracy, and spatial resolution significantly improved, it takes 40 min to implement the NLM denoising algorithm for a BGS image with 200 × 100,000 points. Processed by the QWT denoising algorithm, although SNR increases to 17.26 dB and frequency uncertainty decreases to 0.24 MHz, a BFS accuracy of only 0.2 MHz can be achieved. Moreover, the spatial resolution is 3 m, which is not affected by the QWT denoising algorithm. It takes less than 32 s to denoise the same raw BGS data. The QWT image denoising technique is suitable for BGS data processing in the BOTDA sensor system. [ABSTRACT FROM AUTHOR]

We derive an analytical solution for the differential gain in Brillouin optical time-domain analysis. The found solution gives insight into the mechanisms leading to the high-spatial and spectral resolution observed in differential schemes. An experimental test has been carried out to validate the analytical solution. [ABSTRACT FROM PUBLISHER]

A novel processing algorithm is demonstrated for time-domain high-resolution Brillouin schemes based on acoustic field preactivation. An iterative method is employed to correct the measured data from spurious effects associated with acoustic wave transients. Based on a model of the stimulated Brillouin scattering in the frequency domain, the spatial resolution degrading features are computed and subtracted from the acquired data. Experimental tests with 20-cm spatial resolution and dark-pulse pumping are reported. [ABSTRACT FROM PUBLISHER]

In this letter, we experimentally demonstrate Brillouin echoes-based distributed optical fiber sensing with centimeter spatial resolution. It is based on a differential phase-shift-keying technique using a single Mach-Zehnder modulator to generate a pump pulse and a π-phase-shifted pulse with an easy and accurate adjustment of delay. The results are compared to those obtained in standard Brillouin echo-distributed sensing system with two optical modulators and clearly show a resolution of 5 cm in a spliced segment between two fibers by applying a π -phase-shifted pulse of 500 ps. [ABSTRACT FROM PUBLISHER]

We carried out distributed measurements of the longitudinal gain of fiber-optical parametric amplifiers using a novel sensing technique based on Brillouin optical time-domain analysis. Using this technique, we successfully characterized different gain behaviors in the linear and the saturation regimes. In addition, we demonstrated the recently predicted gain reciprocity at opposite ends of the amplifier span [ABSTRACT FROM PUBLISHER]

An iterative deconvolution technique jointly with an original experimental setup is demonstrated as a useful tool for accuracy enhancement in fiber-optic distributed temperature sensors based on Brillouin optical time-domain analysis measurements. [ABSTRACT FROM PUBLISHER]

To address the issues of high time consumption of frame synchronization involved in a scanning-free Brillouin optical time-domain analysis (SF-BOTDA) system, a fast frame synchronization algorithm based on incremental updating was proposed. In comparison to the standard frame synchronization algorithm, the proposed one significantly reduced the processing time required for the BOTDA system frame synchronization by about 98%. In addition, to further accelerate the real-time performance of frame synchronization, a field programmable gate array (FPGA) hardware implementation architecture based on parallel processing and pipelining mechanisms was also proposed. Compared with the software implementation, it further raised the processing speed by 13.41 times. The proposed approach could lay a foundation for the BOTDA system in the field with the associated high real-time requirements. [ABSTRACT FROM AUTHOR]