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Journal articles on the topic 'Brillouin optical time-domain analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 7 February 2022

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1

Fang, Jian, Miao Sun, Di Che, et al. "Complex Brillouin Optical Time-Domain Analysis." Journal of Lightwave Technology 36, no. 10 (2018): 1840–50. http://dx.doi.org/10.1109/jlt.2018.2792440.

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2

Horiguchi, Tsuneo, Yuki Masui, and Mohd Zan. "Analysis of Phase-Shift Pulse Brillouin Optical Time-Domain Reflectometry." Sensors 19, no. 7 (2019): 1497. http://dx.doi.org/10.3390/s19071497.

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Distributed strain and temperature can be measured by using local Brillouin backscatter in optical fibers based on the strain and temperature dependence of the Brillouin frequency shift. The technique of analyzing the local Brillion backscatter in the time domain is called Brillouin optical time domain reflectometry (BOTDR). Although the best spatial resolution of classic BOTDR remains at around 1 m, some recent BOTDR techniques have attained as high as cm-scale spatial resolution. Our laboratory has proposed and demonstrated a high-spatial-resolution BOTDR called phase-shift pulse BOTDR (PSP-BOTDR), using a pair of probe pulses modulated with binary phase-shift keying. PSP-BOTDR is based on the cross-correlation of Brillouin backscatter and on the subtraction of cross-correlations obtained from the Brillouin scatterings evoked by each phase-modulated probe pulse. Although PSP-BOTDR has attained 20-cm spatial resolution, the spectral analysis method of PSP-BOTDR has not been discussed in detail. This article gives in-depth analysis of the Brillouin backscatter and the correlations of the backscatters of the PSP-BOTDR. Based on the analysis, we propose new spectral analysis methods for PSP-BOTDR. The analysis and experiments show that the proposed methods give better frequency resolution than before.

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3

Zeni, L., L. Picarelli, B. Avolio, et al. "Brillouin optical time-domain analysis for geotechnical monitoring." Journal of Rock Mechanics and Geotechnical Engineering 7, no. 4 (2015): 458–62. http://dx.doi.org/10.1016/j.jrmge.2015.01.008.

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4

Zhou, Da-Peng, Wei Peng, Liang Chen, and Xiaoyi Bao. "Brillouin optical time-domain analysis via compressed sensing." Optics Letters 43, no. 22 (2018): 5496. http://dx.doi.org/10.1364/ol.43.005496.

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5

Zhang, Jianzhong, Yahui Wang, Mingjiang Zhang, et al. "Time-gated chaotic Brillouin optical correlation domain analysis." Optics Express 26, no. 13 (2018): 17597. http://dx.doi.org/10.1364/oe.26.017597.

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6

Song, Kwang Yong, and Hyuk Jin Yoon. "High-resolution Brillouin optical time domain analysis based on Brillouin dynamic grating." Optics Letters 35, no. 1 (2009): 52. http://dx.doi.org/10.1364/ol.35.000052.

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7

Peled, Yair, Avi Motil, and Moshe Tur. "Fast Brillouin optical time domain analysis for dynamic sensing." Optics Express 20, no. 8 (2012): 8584. http://dx.doi.org/10.1364/oe.20.008584.

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8

Kim, Young Hoon, and Kwang Yong Song. "Tailored pump compensation for Brillouin optical time-domain analysis with distributed Brillouin amplification." Optics Express 25, no. 13 (2017): 14098. http://dx.doi.org/10.1364/oe.25.014098.

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9

Vedadi, A., D. Alasia, E. Lantz, et al. "Brillouin Optical Time-Domain Analysis of Fiber-Optic Parametric Amplifiers." IEEE Photonics Technology Letters 19, no. 3 (2007): 179–81. http://dx.doi.org/10.1109/lpt.2006.890039.

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10

Mompó, Juan José, Javier Urricelqui, and Alayn Loayssa. "Brillouin optical time-domain analysis sensor with pump pulse amplification." Optics Express 24, no. 12 (2016): 12672. http://dx.doi.org/10.1364/oe.24.012672.

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11

Mariñelarena, Jon, Haritz Iribas, and Alayn Loayssa. "Pulse coding linearization for Brillouin optical time-domain analysis sensors." Optics Letters 43, no. 22 (2018): 5607. http://dx.doi.org/10.1364/ol.43.005607.

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12

Minardo, Aldo, Ester Catalano, and Luigi Zeni. "Cost-effective method for fast Brillouin optical time-domain analysis." Optics Express 24, no. 22 (2016): 25424. http://dx.doi.org/10.1364/oe.24.025424.

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13

Zhang, Jianzhong, Mingtao Zhang, Mingjiang Zhang, et al. "Chaotic Brillouin optical correlation-domain analysis." Optics Letters 43, no. 8 (2018): 1722. http://dx.doi.org/10.1364/ol.43.001722.

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14

Urricelqui, Javier, Mikel Sagues, and Alayn Loayssa. "Brillouin optical time-domain analysis sensor assisted by Brillouin distributed amplification of pump pulses." Optics Express 23, no. 23 (2015): 30448. http://dx.doi.org/10.1364/oe.23.030448.

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15

Ryu, Gukbeen, Gyu-Tae Kim, Kwang Yong Song, Sang Bae Lee, and Kwanil Lee. "Linearly Configured Brillouin Optical Correlation Domain Analysis System Incorporating Time-Domain Data Processing." Journal of Lightwave Technology 37, no. 18 (2019): 4728–33. http://dx.doi.org/10.1109/jlt.2019.2919448.

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16

Karapanagiotis, Christos, Aleksander Wosniok, Konstantin Hicke, and Katerina Krebber. "Time-Efficient Convolutional Neural Network-Assisted Brillouin Optical Frequency Domain Analysis." Sensors 21, no. 8 (2021): 2724. http://dx.doi.org/10.3390/s21082724.

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To our knowledge, this is the first report on a machine-learning-assisted Brillouin optical frequency domain analysis (BOFDA) for time-efficient temperature measurements. We propose a convolutional neural network (CNN)-based signal post-processing method that, compared to the conventional Lorentzian curve fitting approach, facilitates temperature extraction. Due to its robustness against noise, it can enhance the performance of the system. The CNN-assisted BOFDA is expected to shorten the measurement time by more than nine times and open the way for applications, where faster monitoring is essential.

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17

Iribas, H., J. Urricelqui, J. Mariñelarena, M. Sagues, and A. Loayssa. "Cost-Effective Brillouin Optical Time-Domain Analysis Sensor Using a Single Optical Source and Passive Optical Filtering." Journal of Sensors 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/8243269.

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We present a simplified configuration for distributed Brillouin optical time-domain analysis sensors that aims to reduce the cost of the sensor by reducing the number of components required for the generation of the two optical waves involved in the sensing process. The technique is based on obtaining the pump and probe waves by passive optical filtering of the spectral components generated in a single optical source that is driven by a pulsed RF signal. The optical source is a compact laser with integrated electroabsorption modulator and the optical filters are based on fiber Bragg gratings. Proof-of-concept experiments demonstrate 1 m spatial resolution over a 20 km sensing fiber with a 0.9 MHz precision in the measurement of the Brillouin frequency shift, a performance similar to that of much more complex setups. Furthermore, we discuss the factors limiting the sensor performance, which are basically related to residual spectral components in the filtering process.

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18

Bin Wang, Bin Wang, Xinyu Fan Xinyu Fan, Jiangbing Du Jiangbing Du, and Zuyuan He Zuyuan He. "Performance enhancement of Brillouin optical correlation domain analysis based on frequency chirp magnification." Chinese Optics Letters 15, no. 12 (2017): 120601. http://dx.doi.org/10.3788/col201715.120601.

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19

Li Yongqian, 李永倩, 张立欣 Zhang Lixin, 李晓娟 Li Xiaojuan, and 杨润润 Yang Runrun. "Performance Improvement Method of Rayleigh Brillouin Optical Time Domain Analysis System." Acta Optica Sinica 37, no. 1 (2017): 0106001. http://dx.doi.org/10.3788/aos201737.0106001.

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20

Li, Yongqian, Lixin Zhang, Hanbai Fan, and Lei Wang. "A self-heterodyne detection Rayleigh Brillouin optical time domain analysis system." Optics Communications 427 (November 2018): 190–95. http://dx.doi.org/10.1016/j.optcom.2018.06.054.

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21

Wylie, Michael T. V., Anthony W. Brown, and Bruce G. Colpitts. "Distributed hot-wire anemometry based on Brillouin optical time-domain analysis." Optics Express 20, no. 14 (2012): 15669. http://dx.doi.org/10.1364/oe.20.015669.

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22

Dong, Yongkang, Dengwang Zhou, and Benzhang Wang. "Brillouin optical time-domain analysis at a high sampling rate (invited)." Journal of Physics: Conference Series 1065 (August 2018): 252009. http://dx.doi.org/10.1088/1742-6596/1065/25/252009.

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23

Zaslawski, Simon, Zhisheng Yang, and Luc Thevenaz. "On the 2D Post-Processing of Brillouin Optical Time-Domain Analysis." Journal of Lightwave Technology 38, no. 14 (2020): 3723–36. http://dx.doi.org/10.1109/jlt.2020.2967091.

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24

Martin-Lopez, Sonia, Mercedes Alcon-Camas, Felix Rodriguez, et al. "Brillouin optical time-domain analysis assisted by second-order Raman amplification." Optics Express 18, no. 18 (2010): 18769. http://dx.doi.org/10.1364/oe.18.018769.

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25

Mufti, A., D. Thomson, D. Inaudi, H. M. Vogel, and D. McMahon. "Crack detection of steel girders using Brillouin optical time domain analysis." Journal of Civil Structural Health Monitoring 1, no. 3-4 (2011): 61–68. http://dx.doi.org/10.1007/s13349-011-0006-8.

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26

Li, Yong-qian, Li-xin Zhang, Han-bai Fan, and Hong Li. "A performance enhanced Rayleigh Brillouin optical time domain analysis sensing system." Optoelectronics Letters 14, no. 2 (2018): 84–87. http://dx.doi.org/10.1007/s11801-018-7241-8.

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27

Li Yongqian, 李永倩, 安琪 An Qi, 李晓娟 Li Xiaojuan, 何玉钧 He Yujun, and 张立欣 Zhang Lixin. "Optical Fiber Sensing Technology Based on Loss Vector Brillouin Optical Time Domain Analysis." Acta Optica Sinica 36, no. 9 (2016): 0906004. http://dx.doi.org/10.3788/aos201636.0906004.

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28

Barkov, Fedor L., Yuri A. Konstantinov, and Anton I. Krivosheev. "A Novel Method of Spectra Processing for Brillouin Optical Time Domain Reflectometry." Fibers 8, no. 9 (2020): 60. http://dx.doi.org/10.3390/fib8090060.

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A new method of Brillouin spectra post-processing, which could be applied in modern distributed optical sensors: Brillouin optical time domain analyzers/reflectometers (BOTDA/BOTDR), has been demonstrated. It operates by means of the correlation analysis performed with special technique («backward-correlation»). It does not need any additional data for time or space averaging and operates with the single spectrum only. We have simulated the method accuracy dependence on signal-to-noise ratio (SNR) and other parameters. It is shown that the new method produces better results at low SNRs than conventional technique, based on finding of Brillouin spectrum maximum, do. These results are in a good agreement with the experiment. Finally, we have estimated the performance of the new method for its application in polarization-BOTDA set-up for a polarization maintaining (PM) fiber modal birefringence distributed study.

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29

Lin, Jia-Bing, Xin-Hong Jia, Shi-Rong Xu, Hui-Liang Ma, Han Wu, and Xi-Yang Wei. "Brillouin optical time-domain analysis enhanced by forward stimulated Brillouin scattering: proof-of-concept demonstration." Applied Physics Express 12, no. 10 (2019): 102014. http://dx.doi.org/10.7567/1882-0786/ab4409.

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30

Yanukovich, T. P., and A. V. Polyakov. "Simulation of Distributed Current Sensor Based on Optical Fiber Deformation." Devices and Methods of Measurements 10, no. 3 (2019): 243–52. http://dx.doi.org/10.21122/2220-9506-2019-10-3-243-252.

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Due to the development of automation and control systems, methods and devices for measuring of electric current large values are of great interest. The aim of the work was to develop a schematic diagram of a distributed current strength sensor based on the Brillouin optical frequency domain analysis; to create a mathematical model of the sensor to demonstrate its work and to calculate the basic parameters of the sensor. To provide the measurement optical fiber with conductive coating is used. Between the current bus, where current is measured, and conductive coating the Ampere force arises. Strain occurs in optical fiber due to this force. Stimulated Brillouin scattering has the strain dependent characteristic frequency. Shift of the characteristic frequency allows to measure current in the bus. To measure the characteristic frequency and the location of its shift Brillouin optical frequency domain analysis is used.The mathematical model of sensor operation based on tree-wave model of stimulated Brillouin scattering is demonstrated. This model allows calculating intensity of optical signal in the fiber in dependence of characteristic frequency shift. Brillouin optical frequency domain analysis uses inverse Fourier transform to obtain pulse response.A schematic diagram of a distributed current sensor based on the method of Brillouin optical frequency domain analysis is presented. An a priori estimate of parameters of the measuring system was carried out on the basis of the mathematical model of stimulated Brillouing scattering in an optical fiber. The spatial resolution of the sensor when determining the length and location of fiber sections was 0.06 m. The resolution of the sensor was 0.22 kA, the maximum value of the current strength was 25 kA. Dependence of the sensor operation at different powers of the laser used was investigated. The refractive index change influence on the result of measurements was estimated.

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31

Wei, Haoyu, Yongjun Wang, Qiming Wang, et al. "New BFS Retrieval Technique for Brillouin Optical Time Domain Analysis Sensor System." Electronics 10, no. 11 (2021): 1334. http://dx.doi.org/10.3390/electronics10111334.

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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.

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32

Zadok, Avi, Eyal Preter, and Yosef London. "Phase-Coded and Noise-Based Brillouin Optical Correlation-Domain Analysis." Applied Sciences 8, no. 9 (2018): 1482. http://dx.doi.org/10.3390/app8091482.

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Correlation-domain analysis has enabled distributed measurements of Brillouin gain spectra along optical fibers with high spatial resolution, up to millimeter-scale. The method relies on the joint modulation of counter-propagating Brillouin pump and signal waves so that their complex envelopes are correlated in select positions only. Brillouin optical correlation-domain analysis was first proposed nearly 20 years ago based on frequency modulation of the two waves. This paper reviews two more recent variants of the concept. In the first, the Brillouin pump and signal waves are co-modulated by high-rate binary phase sequences. The scheme eliminates restricting trade-offs between the spatial resolution and the range of unambiguous measurements, and may also suppress noise due to residual Brillouin interactions outside the correlation peak. Sensor setups based on phase coding addressed 440,000 high-resolution points and showed potential for reaching over 2 million such points. The second approach relies on the amplified spontaneous emission of optical amplifiers, rather than the modulation of an optical carrier, as the source of Brillouin pump and signal waves. Noise-based correlation-domain analysis reaches sub-millimeter spatial resolution. The application of both techniques to tapered micro-fibers and planar waveguides is addressed as well.

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33

Pang, Chao, Zijie Hua, Dengwang Zhou, et al. "Opto-mechanical time-domain analysis based on coherent forward stimulated Brillouin scattering probing." Optica 7, no. 2 (2020): 176. http://dx.doi.org/10.1364/optica.381141.

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34

Farahani, Mohsen Amiri, Eduardo Castillo-Guerra, and Bruce G. Colpitts. "Accurate estimation of Brillouin frequency shift in Brillouin optical time domain analysis sensors using cross correlation." Optics Letters 36, no. 21 (2011): 4275. http://dx.doi.org/10.1364/ol.36.004275.

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35

Xu, Pengbai, Yongkang Dong, Dengwang Zhou, et al. "1200°C high-temperature distributed optical fiber sensing using Brillouin optical time domain analysis." Applied Optics 55, no. 21 (2016): 5471. http://dx.doi.org/10.1364/ao.55.005471.

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36

Zhou, Zhi, Jianping He, Kai Yan, and Jinping Ou. "Fiber-reinforced polymer-packaged optical fiber sensors based on Brillouin optical time-domain analysis." Optical Engineering 47, no. 1 (2008): 014401. http://dx.doi.org/10.1117/1.2835599.

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37

Li, Zonglei, Zhisheng Yang, Lianshan Yan, Marcelo A. Soto, and Luc Thévenaz. "Hybrid Golay-coded Brillouin optical time-domain analysis based on differential pulses." Optics Letters 43, no. 19 (2018): 4574. http://dx.doi.org/10.1364/ol.43.004574.

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38

Soto, Marcelo A., Gabriele Bolognini, Fabrizio Di Pasquale, and Luc Thévenaz. "Long-range Brillouin optical time-domain analysis sensor employing pulse coding techniques." Measurement Science and Technology 21, no. 9 (2010): 094024. http://dx.doi.org/10.1088/0957-0233/21/9/094024.

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39

Minardo, Aldo, Agnese Coscetta, Romeo Bernini, and Luigi Zeni. "Heterodyne slope-assisted Brillouin optical time-domain analysis for dynamic strain measurements." Journal of Optics 18, no. 2 (2016): 025606. http://dx.doi.org/10.1088/2040-8978/18/2/025606.

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40

Minardo, Aldo, Agnese Coscetta, Romeo Bernini, and Luigi Zeni. "Brillouin Optical Time Domain Analysis in Silica Fibers at 850-nm Wavelength." IEEE Photonics Technology Letters 28, no. 22 (2016): 2577–80. http://dx.doi.org/10.1109/lpt.2016.2605739.

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41

Feng, Cheng, Hari Datta Bhatta, Jonathan Bohbot, et al. "Gain Spectrum Engineering in Slope-Assisted Dynamic Brillouin Optical Time-Domain Analysis." Journal of Lightwave Technology 38, no. 24 (2020): 6967–75. http://dx.doi.org/10.1109/jlt.2020.3021796.

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42

Thévenaz, Luc, Stella Foaleng Mafang, and Jie Lin. "Effect of pulse depletion in a Brillouin optical time-domain analysis system." Optics Express 21, no. 12 (2013): 14017. http://dx.doi.org/10.1364/oe.21.014017.

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43

Chu, Qi, Benzhang Wang, Henan Wang, Dexin Ba, and Yongkang Dong. "Fast Brillouin optical time-domain analysis using frequency-agile and compressed sensing." Optics Letters 45, no. 15 (2020): 4365. http://dx.doi.org/10.1364/ol.397884.

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44

Dominguez-Lopez, Alejandro, Xabier Angulo-Vinuesa, Alexia Lopez-Gil, Sonia Martin-Lopez, and Miguel Gonzalez-Herraez. "Non-local effects in dual-probe-sideband Brillouin optical time domain analysis." Optics Express 23, no. 8 (2015): 10341. http://dx.doi.org/10.1364/oe.23.010341.

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45

Tsuji, Kenichiro, Hitoshi Noda, and Noriaki Onodera. "Sweep-free brillouin optical time domain analysis using two individual laser sources." Optical Review 19, no. 6 (2012): 381–87. http://dx.doi.org/10.1007/s10043-012-0062-2.

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46

Gao, Xia, Xiaobin Hong, Sheng Wang, Xizi Sun, Liangming Xiong, and Jian Wu. "Single-Fiber-Based Brillouin Optical Time Domain Analysis With Far-End Modulation." Journal of Lightwave Technology 39, no. 11 (2021): 3607–13. http://dx.doi.org/10.1109/jlt.2021.3069231.

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47

Nordin, Nur Dalilla, Mohd Saiful Dzulkefly Zan, and Fairuz Abdullah. "Comparative Analysis on the Deployment of Machine Learning Algorithms in the Distributed Brillouin Optical Time Domain Analysis (BOTDA) Fiber Sensor." Photonics 7, no. 4 (2020): 79. http://dx.doi.org/10.3390/photonics7040079.

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This paper demonstrates a comparative analysis of five machine learning (ML) algorithms for improving the signal processing time and temperature prediction accuracy in Brillouin optical time domain analysis (BOTDA) fiber sensor. The algorithms analyzed were generalized linear model (GLM), deep learning (DL), random forest (RF), gradient boosted trees (GBT), and support vector machine (SVM). In this proof-of-concept experiment, the performance of each algorithm was investigated by pairing Brillouin gain spectrum (BGS) with its corresponding temperature reading in the training dataset. It was found that all of the ML algorithms have significantly reduced the signal processing time to be between 3.5 and 655 times faster than the conventional Lorentzian curve fitting (LCF) method. Furthermore, the temperature prediction accuracy and temperature measurement precision made by some algorithms were comparable, and some were even better than the conventional LCF method. The results obtained from the experiments would provide some general idea in deploying ML algorithm for characterizing the Brillouin-based fiber sensor signals.

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48

Hotate, Kazuo. "Brillouin Optical Correlation-Domain Technologies Based on Synthesis of Optical Coherence Function as Fiber Optic Nerve Systems for Structural Health Monitoring." Applied Sciences 9, no. 1 (2019): 187. http://dx.doi.org/10.3390/app9010187.

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Brillouin optical correlation-domain technologies are reviewed as “fiber optic nerve systems” for the health monitoring of large structures such as buildings, bridges, and aircraft bodies. The Brillouin scattering property is used as a sensing mechanism for strain and/or temperature. Continuous lightwaves are used in the technologies, and their optical coherence properties are synthesized to realize position-selective measurement. This coherence manipulation technology is called the “synthesis of optical coherence function (SOCF)”. By utilizing SOCF technologies, stimulated Brillouin scattering is generated position-selectively along the fiber, which is named “Brillouin optical correlation domain analysis (BOCDA)”. Spontaneous Brillouin scattering, which takes place at any portion along the fiber, can also be measured position-selectively by the SOCF technology. This is called “Brillouin optical correlation domain reflectometry (BOCDR)”. When we use pulsed lightwaves that have the position information, sensing performances, such as the spatial resolution, are inherently restricted due to the Brillouin scattering nature. However, in the correlation-domain technologies, such difficulties can be reduced. Superior performances have been demonstrated as distribution-sensing mechanisms, such as a 1.6-mm high spatial resolution, a fast measurement speed of 5000 points/s, and a 7000-με strain dynamic range, individually. The total performance of the technologies is also discussed in this paper. A significant feature of the technologies is their random accessibility to discrete multiple points that are selected arbitrarily along the fiber, which is not realized by the time domain pulsed-lightwave technologies. Discriminative and distributed strain/temperature measurements have also been realized using both the BOCDA technology and Brillouin dynamic grating (BDG) phenomenon, which are associated with the stimulated Brillouin scattering process. In this paper, the principles, functions, and applications of the SOCF, BOCDA, BOCDR, and BDG-BOCDA systems are reviewed, and their historical aspects are also discussed.

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49

Jeong, Ji Ho, Kwanil Lee, Kwang Yong Song, Je-Myung Jeong, and Sang Bae Lee. "Bidirectional measurement for Brillouin optical correlation domain analysis." Optics Express 20, no. 10 (2012): 11091. http://dx.doi.org/10.1364/oe.20.011091.

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50

Kwang-Yong Song and K. Hotate. "Brillouin Optical Correlation Domain Analysis in Linear Configuration." IEEE Photonics Technology Letters 20, no. 24 (2008): 2150–52. http://dx.doi.org/10.1109/lpt.2008.2007744.

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