Brillouin Frequency Shift Measurement Research Articles

Brillouin frequency shift measurement by zero-crossing point search in virtually synthesized spectra of Brillouin gain and loss

We demonstrate a method for fast and precise Brillouin frequency shift measurement based on searching for the zero-crossing point of a virtually composed spectrum of Brillouin gain and loss obtained by a dual-frequency probe beam. Simulations and experiments show that searching for the zero-crossing point of a virtually synthesized Brillouin gain spectrum can be easily done without a large error compared with peak search of the Brillouin gain spectrum in the conventional method.

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.

A Brillouin scattering-based fast temperature measurement method for ADSS of distribution IoT in electricity

In order to decrease time of temperature measurement for optical fiber in ADSS (all-dielectric self-supporting cable) of distribution IoT (Internet of Things) in electricity, the slope-assisted method is applied to its temperature demodulation. According to the introduction of the Brillouin scattering-based optical fiber temperature measurement method, the basic principle of Brillouin frequency shift measurement method based on the spectra fitting algorithm and the slope-assisted method is analyzed. Based on simulated Brillouin spectra with different signal-to-noise ratios (SNRs), the measurement time and accuracy of the spectra fitting algorithm and the slope-assisted method are compared. The results indicate that when if the SNR of Brillouin spectra is not less than 35 dB, the mean error of temperature measurement by the slope-assisted method is less than 0.5°C, which is slightly larger than the error of the spectra fitting algorithm, but the spectra measurement time is only 1/17 of that of the latter.

Improving Prediction Accuracy and Extraction Precision of Frequency Shift from Low-SNR Brillouin Gain Spectra in Distributed Structural Health Monitoring

In this paper, we studied the possibility of increasing the Brillouin frequency shift (BFS) detection accuracy in distributed fibre-optic sensors by the separate and joint use of different algorithms for finding the spectral maximum: Lorentzian curve fitting (LCF, including the Levenberg–Marquardt (LM) method), the backward correlation technique (BWC) and a machine learning algorithm, the generalized linear model (GLM). The study was carried out on real spectra subjected to the subsequent addition of extreme digital noise. The precision and accuracy of the LM and BWC methods were studied by varying the signal-to-noise ratios (SNRs) and by incorporating the GLM method into the processing steps. It was found that the use of methods in sequence gives a gain in the accuracy of determining the sensor temperature from tenths to several degrees Celsius (or MHz in BFS scale), which is manifested for signal-to-noise ratios within 0 to 20 dB. We have found out that the double processing (BWC + GLM) is more effective for positive SNR values (in dB): it gives a gain in BFS measurement precision near 0.4 °C (428 kHz or 9.3 ); for BWC + GLM, the difference of precisions between single and double processing for SNRs below 2.6 dB is about 1.5 °C (1.6 MHz or 35 ). In this case, double processing is more effective for all SNRs. The described technique’s potential application in structural health monitoring (SHM) of concrete objects and different areas in metrology and sensing were also discussed.

Improving the Brillouin frequency shift measurement resolution in the Brillouin optical time domain reflectometry (BOTDR) fiber sensor by artificial neural network (ANN)

We propose to use an artificial neural network (ANN) model to improve the Brillouin frequency shift (BFS) resolution of the sub-meter spatial resolution differential cross-spectrum Brillouin optical time domain reflectometry (DCS-BOTDR) fiber sensor. ANN technique was chosen due its nonlinear mapping characteristic that makes it suitable to effectively extract the BFS distribution along the fiber optic. Importantly, the ANN model offers more flexibility in estimating the BFS because one does not need to set the initial parameters like the conventional polynomial function based on Lorentzian curve fitting (LCF) model. In our ANN model, we used the BFS distribution data measured by the pulse duration TL = 14 ns at 56,000 times averaging as the ground truth in the training phase, because they provided the highest BFS resolution compared to that of obtained by other pulse duration cases, as reported previously. After training the data, we tested them with the BFS distribution results for TL = 2, 4 and 60 ns cases, which they showed poor BFS resolution when processed by the conventional model. For TL = 2 and 4 ns cases, the deployment of ANN has significantly improved the BFS resolution at least two times higher than that by the conventional polynomial fitting. Surprisingly, for TL = 60 ns case, despite the reduced number of averaging from 56,000 to 7000 times (i.e., eight times faster measurement), the BFS resolution has improved about seven times from 21.13 MHz to 2.88 MHz. This indicates the significant contribution of the ANN model in reducing the measurement time in the DCS-BOTDR

Extracting Brillouin frequency shift accurately based on particle swarm optimization and a cross-correlation method.

A fitting algorithm based on particle swarm optimization (PSO) and the cross-correlation method (XCM) was proposed to accurately extract features of the Brillouin scattering spectrum. Both the simulation and experiment were conducted to verify the validity of the proposed algorithm. The results show that the algorithm achieves high demodulation accuracy and is suitable for Brillouin scattering spectra with different signal-to-noise ratios, full width at half-maximums, frequency sweep intervals, and spectral symmetries. Compared with the Lorenz curve fitting and XCM algorithm, the extraction error of the PSO-XCM can be optimized up to 99.98% and 99.93%, and the fitting degree can be improved by 98%. Moreover, based on the proposed algorithm, the minimum temperature measurement error can reach 0.06°C and the Brillouin frequency shift measurement error is 0.07 MHz in 10 km sensing fiber for the Brillouin optical time domain analysis (BOTDA) sensing system.

Single-shot chirped pulse BOTDA for static and dynamic strain sensing.

Driven by the strong need for distributed high-frequency dynamic strain sensing, ultra-fast Brillouin optical time-domain analysis is rapidly becoming a vital technique. Thus, in this Letter, we propose and demonstrate a novel method by using a chirped pulse as a pump signal to extract the relative Brillouin frequency shift (BFS) changes through the real-time delays between adjacent Brillouin traces; this enables static and dynamic strain measurement without time-consuming frequency sweeping process. Benefiting from single-shot measurement based on Brillouin traces, the system has a high acquisition rate that is only limited by the sensor length without averaging, and is immune to the polarization fading problem, thanks to electrical delay time measurement. The pump source is a 1 MHz linewidth laser without a phase-locking loop; the laser frequency drifting noise could be compensated by the signal from the non-disturbed fiber section. In the experiments, BFS measurement resolution of 0.42 MHz with 4.5 m spatial resolution is demonstrated over a 5 km non-uniform fiber.

Fast Measurement of Brillouin Frequency Shift in Optical Fiber Based on a Novel Feedforward Neural Network

Brillouin scattering-based distributed optical fiber sensors have been successfully employed in various applications in recent decades, because of benefits such as small size, light weight, electromagnetic immunity, and continuous monitoring of temperature and strain. However, the data processing requirements for the Brillouin Gain Spectrum (BGS) restrict further improvement of monitoring performance and limit the application of real-time measurements. Studies using Feedforward Neural Network (FNN) to measure Brillouin Frequency Shift (BFS) have been performed in recent years to validate the possibility of improving measurement performance. In this work, a novel FNN that is 3 times faster than previous FNNs is proposed to improve BFS measurement performance. More specifically, after the original Brillouin Gain Spectrum (BGS) is preprocessed by Principal Component Analysis (PCA), the data are fed into the Feedforward Neural Network (FNN) to predict BFS.

Segmented Noise Reduction Based on Brillouin-Spectrum-Partition in Brillouin Optical Time Domain Sensors

In this paper, the necessity of segmented image denoising in the signal post-processing of Brillouin Optical Time Domain sensors (BOTDS) is investigated firstly, then a novel cross-correlation based Brillouin-spectrum-partition (BSP) method is proposed to denoise the noisy Brillouin gain or loss spectrum in BOTDS. In the BSP filter, the non-correlation factors of adjacent Brillouin scattering spectrum are firstly computed, then the Brillouin spectrum along the fiber is divided into transition sub-images with large changes in Brillouin frequency shift (BFS) and non-transition sub-images with small changes in BFS, and finally the transition and non-transition sub-images are filtered with linear and non-linear filters, respectively. By using an 800m-length G657 sensing fiber with five temperature events in a proof-of-concept experiment, a BFS measurement accuracy improvement of 22% in non-transition section, and a spatial resolution (SR) enhancement of 84% in transition Section can be achieved by using the proposed BSP filter, compared to the results obtained by using non-local means (NLM) filter. Besides, a BFS measurement accuracy improvement of 54% in non-transition section, and a SR enhancement of 71% in transition section, can be achieved compared with the results obtained by using Gaussian filter. Moreover, to deal with the noisy Brillouin spectrum of the 800m-length fiber by using the proposed BSP filter, we obtain a processing time reduction of 37% compared with that by using NLM filter.

Neural network-assisted signal processing in Brillouin optical correlation-domain sensing for potential high-speed implementation.

The general neural networks (NNs) based on classification convert the Brillouin frequency shift (BFS) extraction in Brillouin-based distributed sensing to a problem in which the possible BFS output of the sensing system belongs to a finite number of discrete values. In this paper, we demonstrate a method of applying NNs with adaptive BFS incremental steps to signal processing for Brillouin optical correlation-domain sensing and achieve higher accuracy and operation speed. The comparison with the conventional curving fitting method shows that the NN improves the BFS measurement accuracy by 2-3 times and accelerates the signal processing speed by 1000 times for simulated signals. The experimental results demonstrate the NN provides 1.6-2.7 times enhancement for BFS measurement accuracy and 5000 times acceleration for the BFS extraction speed. This method supplies a potential solution to online signal processing for real-time Brillouin sensing.

Overcoming EDFA slow transient effect in a Golay-coded BOTDA sensor by a distributed depletion mapping method.

The erbium-doped-fiber-amplifier (EDFA), generally served as a pre-amplifier, could effectively raise the signal-to-noise ratio (SNR) of a Brillouin optical time-domain analysis (BOTDA) sensor. However, it also induces a distortion in the Brillouin gain spectrum and Brillouin frequency shift measurement errors due to the slow transient effect (STE) in the coded-BOTDA. We propose a distributed depletion mapping (DDM) method to overcome such an effect. A continuous light wave with a particular wavelength is injected to map the STE-induced depletion to compensate for the distortion. The proposed scheme is experimentally demonstrated along a 120-km sensing fiber with 2-m spatial resolution. Experimental results show that the conventional tail-alignment (TA) method cannot compensate for the STE over the whole fiber link, while the proposed DDM method compensates for over 7.69-MHz measurement errors.

Phase fluctuation cancellation for coherent-detection BOTDA fiber sensors based on optical subcarrier multiplexing.

The employment of coherent detection in a Brillouin optical time domain analysis (BOTDA) fiber sensor brings benefits, including signal-to-noise ratio enhancement, non-local effect reduction, and sensing speed improvement. Recently, it was found that the performance of a coherent-detection BOTDA fiber sensor suffers from phase fluctuations introduced by the fiber group delay jitter. Here, we propose a phase fluctuation cancellation approach based on optical subcarrier multiplexing. In a proof-of-concept experiment, the phase stability for in-phase/quadrature demodulation reaches a standard deviation value of as small as 0.4 mrad. The variations in the Brillouin gain and phase spectra caused by the phase fluctuation are then effectively alleviated, resulting in an enhancement of the Brillouin frequency shift measurement certainty along the whole sensing fiber.

Noise reduction by Brillouin spectrum reassembly in Brillouin optical time domain sensors

In this paper, we present a novel image-processing based spectrum reassembly method to handle the noisy Brillouin gain or loss spectrum in Brillouin optical time domain sensors. The principle of the proposed Brillouin-spectrum-reassembly (BSR) Filter, is firstly dividing the Brillouin spectrum along the fiber into several segments according to the differences of Brillouin frequency shift (BFS), then shifting the Brillouin spectrum to reassemble a new image with equal BFSs and filtering the image by a conventional filter, finally shifting the Brillouin spectrum of each segment in the opposite direction to obtain the filtered Brillouin spectrum. Since the size of the filter windows in the reassembled image can be reduced greatly, the total processing time is decreased effectively. Furthermore, the BFS measurement accuracy and spatial resolution can be enhanced due to the edge-preserving image filtering strategy of the method. The measurement performance and processing speed improvements are verified by simulation and experiment. Utilizing a Brillouin optical time domain reflectometry (BOTDR) sensor, we achieve a BFS measurement accuracy improvement of 13%, a spatial resolution improvement of 46% and a processing time reduce of 35% in a 5.2 km-length G657 fiber by use of the proposed method, as compared with an excellent spectrum non-reassembly filtering method.

The Influence of Laser Linewidth on the Brillouin Shift Frequency Accuracy of BOTDR

This paper analyzes the influence of laser linewidth on the measurement accuracy of a frequency-scanning Brillouin optical time domain reflectometer (FS-BOTDR), allowing for both the width of Brillouin gain spectrum and the signal-to-noise ratio (SNR) of the BOTDR system. The measurement accuracy of the Brillouin frequency shift (BFS) is theoretically investigated versus the duration of the probe pulse and the linewidth of the laser source, by numerically simulating how a FS-BOTDR works and evaluating the Brillouin gain spectrum (BGS) width and the system SNR. The simulation results show that the BFS accuracy is improved as the laser linewidth becomes narrower when the probe pulse width is fixed. We utilize five types of lasers with respective linewidths of 1.05 MHz, 101 kHz, 10.2 kHz, 3.1 kHz, and 98 Hz to compare the BFS measurement accuracy over a ~10 km optical sensing fiber. The experimental results demonstrate that the root-mean-square error (RMSE) of BFS decreases with the laser linewidth narrowing from 1.05 MHz to 3.1 kHz, which is in good agreement with the numerical simulation. However, the RMSE of BFS increases when the laser linewidth is less than 3.1 kHz, which may arise from the coherent Rayleigh noise due to a too narrow laser linewidth. The results can provide a theoretical basis and experimental guidance for choosing the appropriate laser linewidth in BOTDR.

Dynamic strain measurement with kHz-level repetition rate and centimeter-level spatial resolution based on Brillouin optical correlation domain analysis.

In this paper, we propose and demonstrate an ultrahigh-speed Brillouin optical correlation domain analysis (BOCDA) with a single-position sampling rate of 200 kS/s and a spatial resolution of 8 cm. The Brillouin gain spectrum (BGS) is obtained by using a data subtraction scheme rather than the conventional lock-in amplifier (LIA) detection configuration, thus removing the limitation of measurement speed imposed by the LIA. Meanwhile, a voltage controlled oscillator (VCO) is used to sweep the frequency interval between the pump and the probe rapidly. As a proof of concept, we implement measurements of various dynamic strains with frequencies up to 20 kHz at arbitrary position. Moreover, to implement high-speed distributed measurements of Brillouin frequency shift (BFS) along the whole fiber under test (FUT), we propose a novel measuring method which moves the correlation peak and sweeps the pump-probe frequency interval simultaneously. A repetition rate of 1 kHz is verified by measuring dynamic strains with frequencies up to 200 Hz, for distributed measurements performed with 200 points.

Brillouin Frequency Shift of Fiber Distributed Sensors Extracted from Noisy Signals by Quadratic Fitting.

It is a basic task in Brillouin distributed fiber sensors to extract the peak frequency of the scattering spectrum, since the peak frequency shift gives information on the fiber temperature and strain changes. Because of high-level noise, quadratic fitting is often used in the data processing. Formulas of the dependence of the minimum detectable Brillouin frequency shift (BFS) on the signal-to-noise ratio (SNR) and frequency step have been presented in publications, but in different expressions. A detailed deduction of new formulas of BFS variance and its average is given in this paper, showing especially their dependences on the data range used in fitting, including its length and its center respective to the real spectral peak. The theoretical analyses are experimentally verified. It is shown that the center of the data range has a direct impact on the accuracy of the extracted BFS. We propose and demonstrate an iterative fitting method to mitigate such effects and improve the accuracy of BFS measurement. The different expressions of BFS variances presented in previous papers are explained and discussed.

Frequency domain staring pump-probe technique for Brillouin gain/loss spectrum measurement.

We propose and demonstrate a modified frequency sweep-free pump-probe technique, called staring pump-probe technique (SPPT) for Brillouin signal measurement based on stimulated Brillouin scattering (SBS). The SPPT retains the advantages of conventional pump-probe technique, and employs a simple device and low-cost measurement system. Moreover, the Brillouin gain/loss spectrum (BGS/BLS) can be reconstructed without frequency-sweep, thus greatly improving the measurement speed. In this paper, an approximate flat-top spectrum broadened probe light is introduced through distributed feedback laser by direct modulation. The BGS/BLS is reconstructed with the enhanced signal-noise ratio of approximately 21dB/23dB. This technique has a potential application for some Brillouin scattering involved Brillouin frequency shift measurement.

Brillouin frequency shift measurement with virtually controlled sensitivity

We propose measuring the change in Brillouin frequency shift (BFS) in an optical fiber with virtually controlled sensitivity based on the Vernier effect using a multimode pump and probe light. We measure BFS from the envelope curve of the spectra for multimode Stokes light without scanning the probe frequency. The sensitivity of BFS is virtually controlled by changing the difference in the mode spacing between the pump and the probe. It is experimentally demonstrated that the virtual sensitivity is controlled from −1.1 to 1.1 GHz/K, the maximum value of which is 1,100 times higher than the standard BFS of 1 MHz/K.

High-accuracy Brillouin frequency shift measurement system based on stimulated Brillouin scattering phase shift

A high-accuracy Brillouin frequency shift (BFS) measurement system for vector Brillouin optical time-domain analysis-based temperature sensor is proposed, in which double sideband modulation is used and the stimulated Brillouin scattering (SBS) gain and loss processes work together to generate a superimposed SBS phase-shift spectrum. The measurement principle is analyzed by mathematical modeling and the proof-of-concept experiment is performed by using a 100-m long standard single-mode fiber. The theoretical and experimental results reveal that the temperature sensitivity of BFS obtained from the measured SBS phase-shift spectrum is 1.059 MHz / ° C , and the measurement error of temperature is only half that in traditional single sideband-based system, which indicates that the proposed technique can realize high-accuracy temperature measurement and have huge potential in the field of long-distance and high-accuracy sensing.

Cyclic coding for Brillouin optical time-domain analyzers using probe dithering.

We study the performance limits of mono-color cyclic coding applied to Brillouin optical time-domain analysis (BOTDA) sensors that use probe wave dithering. BOTDA analyzers with dithering of the probe use a dual-probe-sideband setup in which an optical frequency modulation of the probe waves along the fiber is introduced. This avoids non-local effects while keeping the Brillouin threshold at its highest level, thus preventing the spontaneous Brillouin scattering from generating noise in the deployed sensing fiber. In these conditions, it is possible to introduce an unprecedented high probe power into the sensing fiber, which leads to an enhancement of the signal-to-noise ratio (SNR) and consequently to a performance improvement of the analyzer. The addition of cyclic coding in these set-ups can further increase the SNR and accordingly enhance the performance. However, this unprecedented probe power levels that can be employed result in the appearance of detrimental effects in the measurement that had not previously been observed in other BOTDA set-ups. In this work, we analyze the distortion in the decoding process and the errors in the measurement that this distortion causes, due to three factors: the power difference of the successive pulses of a code sequence, the appearance of first-order non-local effects and the non-linear amplification of the probe wave that results when using mono-color cyclic coding of the pump pulses. We apply the results of this study to demonstrate the performance enhancement that can be achieved in a long-range dithered dual-probe BOTDA. A 164-km fiber-loop is measured with 1-m spatial resolution, obtaining 3-MHz Brillouin frequency shift measurement precision at the worst contrast location. To the best of our knowledge, this is the longest sensing distance achieved with a BOTDA sensor using mono-color cyclic coding.