• Opto-Electronic Advances
  • Vol. 5, Issue 3, 200078 (2022)
Shuaiqi Liu1, Feihong Yu1, Rui Hong2, Weijie Xu1, Liyang Shao1、*, and Feng Wang2、*
Author Affiliations
  • 1Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen 518000, China
  • 2Key Laboratory of Intelligent Optical Sensing and Manipulation, Ministry of Education, Nanjing University, Nanjing 210023, China
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    DOI: 10.29026/oea.2022.200078 Cite this Article
    Shuaiqi Liu, Feihong Yu, Rui Hong, Weijie Xu, Liyang Shao, Feng Wang. Advances in phase-sensitive optical time-domain reflectometry[J]. Opto-Electronic Advances, 2022, 5(3): 200078 Copy Citation Text show less
    The setup of DVS-Φ-OTDR system based on direct detection.
    Fig. 1. The setup of DVS-Φ-OTDR system based on direct detection.
    The setup of DAS-Φ-OTDR system with different demodulation methods.(a) Heterodyne detection + IQ phase demodulation. (b) Heterodyne detection + Hilbert transform phase demodulation. (c) Direct detection + phase demodulation based on a 3×3 coupler. (d) Direct detection + phase demodulation based on PGC.
    Fig. 2. The setup of DAS-Φ-OTDR system with different demodulation methods.(a) Heterodyne detection + IQ phase demodulation. (b) Heterodyne detection + Hilbert transform phase demodulation. (c) Direct detection + phase demodulation based on a 3×3 coupler. (d) Direct detection + phase demodulation based on PGC.
    Operation principle of Φ-OTDR based VSP monitoring system. (a) Zero-offset VSP. (b) Walk-away VSP.
    Fig. 3. Operation principle of Φ-OTDR based VSP monitoring system. (a) Zero-offset VSP. (b) Walk-away VSP.
    (a) Normalized strain (green curve) recorded during an Mb ~6.2 (USGS) earthquake (Kota Ternate, Indonesia, 2015-03-17 22:12:28 UTC, 1.669°N; 126.522°E, 44 km depth) superimposed with the normalized velocity record (red curve) from the broadband station RAH (80 m from the optical cable). (b) Zoom-view from (a) showing a good phase correspondence between seismometer velocity record and DAS strain records at a 20s period. (c) Short record (6 s) of strain phases from a local earthquake trapped in the fault damage zone. Waves inside and outside the fault zone have different apparent velocities. Figures reproduced from ref.98, under a Creative Commons Attribution 4.0 International License.
    Fig. 4. (a) Normalized strain (green curve) recorded during an Mb ~6.2 (USGS) earthquake (Kota Ternate, Indonesia, 2015-03-17 22:12:28 UTC, 1.669°N; 126.522°E, 44 km depth) superimposed with the normalized velocity record (red curve) from the broadband station RAH (80 m from the optical cable). (b) Zoom-view from (a) showing a good phase correspondence between seismometer velocity record and DAS strain records at a 20s period. (c) Short record (6 s) of strain phases from a local earthquake trapped in the fault damage zone. Waves inside and outside the fault zone have different apparent velocities. Figures reproduced from ref.98, under a Creative Commons Attribution 4.0 International License.
    (a) Stacked DAS beam trace (black) filtered to various bands between 0.02 and 1 Hz compared with amplitude-normalized particle velocity from a broadband seismometer rotated into the mean azimuth of the DAS array (red). (b) Separation of ocean and seismic waves in the first quadrant of the logarithmic space of the Φ-OTDR signal frequency-wave number domain. Figures reproduced from ref.101, under a Creative Commons Attribution 4.0 International License.
    Fig. 5. (a) Stacked DAS beam trace (black) filtered to various bands between 0.02 and 1 Hz compared with amplitude-normalized particle velocity from a broadband seismometer rotated into the mean azimuth of the DAS array (red). (b) Separation of ocean and seismic waves in the first quadrant of the logarithmic space of the Φ-OTDR signal frequency-wave number domain. Figures reproduced from ref.101, under a Creative Commons Attribution 4.0 International License.
    Ambient noise based, cross-correlation computed between all Φ-OTDR traces of the cable with respect to one arbitrary trace (at position ~11.5 km) showing several geological features. Figure reproduced from supplementary material of ref.98 under a Creative Commons Attribution 4.0 International License.
    Fig. 6. Ambient noise based, cross-correlation computed between all Φ-OTDR traces of the cable with respect to one arbitrary trace (at position ~11.5 km) showing several geological features. Figure reproduced from supplementary material of ref.98 under a Creative Commons Attribution 4.0 International License.
    Experimental site layout. Figure reproduced from ref.103, under a Creative Commons Attribution 4.0 International License.
    Fig. 7. Experimental site layout. Figure reproduced from ref.103, under a Creative Commons Attribution 4.0 International License.
    Fiber cable layout and operation principle of 1D-CNN. Figure redrawn after ref.192.
    Fig. 8. Fiber cable layout and operation principle of 1D-CNN. Figure redrawn after ref.192.
    An illustration of the railway safety monitoring experiments. Figure reproduced from ref.108, under the OSA Open Access Publishing Agreement.
    Fig. 9. An illustration of the railway safety monitoring experiments. Figure reproduced from ref.108, under the OSA Open Access Publishing Agreement.
    Fiber cable layout alongside railways. Figure redrawn after ref.113.
    Fig. 10. Fiber cable layout alongside railways. Figure redrawn after ref.113.
    Integration of Φ-OTDR system in the DWDM communication network. Figure reproduced with permission from ref.116, IEEE.
    Fig. 11. Integration of Φ-OTDR system in the DWDM communication network. Figure reproduced with permission from ref.116, IEEE.
    Experimental setup for discharge detection with two acoustic transducers attached to the 40 kV joint. (Figure redrawn after ref. 119)
    Fig. 12. Experimental setup for discharge detection with two acoustic transducers attached to the 40 kV joint. (Figure redrawn after ref. 119)
    Fiber deployment inside or outside electrical cable. (Figure redrawn after ref. 120)
    Fig. 13. Fiber deployment inside or outside electrical cable. (Figure redrawn after ref. 120)
    (a) Fiber coil transducer deployment on the GIS device. (b) Detected discharge signal of transducer #1, #2 and #3 at pulse repetition rate of 10 kHz. Figure reproduced from ref. 121, under a Creative Commons Attribution 4.0 International License.
    Fig. 14. (a) Fiber coil transducer deployment on the GIS device. (b) Detected discharge signal of transducer #1, #2 and #3 at pulse repetition rate of 10 kHz. Figure reproduced from ref. 121, under a Creative Commons Attribution 4.0 International License.
    (a) Φ-OTDR system configuration. (b) Tree infestation sensing results. (Figure reproduced from ref.182, under a Creative Commons Attribution 4.0 International License.
    Fig. 15. (a) Φ-OTDR system configuration. (b) Tree infestation sensing results. (Figure reproduced from ref.182, under a Creative Commons Attribution 4.0 International License.
    (a) Cross section of the MCF. The circled fiber cores were selected for bending direction analysis. (b) Fiber bending direction analysis in the x-y-ε space. The x-yplane corresponds to one cross section of the MCF. Figure reproduced from ref.181, under the OSA Open Access Publishing Agreement.
    Fig. 16. (a) Cross section of the MCF. The circled fiber cores were selected for bending direction analysis. (b) Fiber bending direction analysis in the x-y-ε space. The x-yplane corresponds to one cross section of the MCF. Figure reproduced from ref.181, under the OSA Open Access Publishing Agreement.
    (a) Operation principle of the Φ-OTDR based solar irradiance sensing system. (b) Temperature difference between the black and reference fiber vs. the applied solar irradiance. Figure reproduced from ref.183, under a Creative Commons Attribution 4.0 International License.
    Fig. 17. (a) Operation principle of the Φ-OTDR based solar irradiance sensing system. (b) Temperature difference between the black and reference fiber vs. the applied solar irradiance. Figure reproduced from ref.183, under a Creative Commons Attribution 4.0 International License.
    ReferenceMethodYearEffect
    ref.15Phase-shifted double pulse2012>20 dB SNR by reducing interference fading
    ref.1310–π binary phase shift + phase-shifted double pulse201946 dB SNR by reducing interference fading
    ref.132Multi-frequency nonlinear frequency modulation pulses201845 dB SNR by reducing interference fading
    ref.40Three different probe frequencies + a tracking algorithm2019The fading effect could be suppressed to 1.15%
    ref.133Single rectangular probe + a novel spectrum extraction and remixing method20197.1 dB SNR improvement by eliminating interference fading
    ref.134Multimode optical fiber + joint independent analysis2016Eliminate interference fading
    ref.135Φ-OTDR system based on uwFBG through an unbalanced 3 × 3 coupler structure201756 dB SNR achievement by reducing interference fading
    ref.136Distinguished the false alarm peak by comparison201611.5 dB SNR improvement by discriminating interference fading
    ref.137PMF2011>2 dB SNR achievement by reducing polarization-dependent noise
    ref.138Polarization diversity scheme201610.9 dB SNR improvement by reducing polarization-dependent noise
    ref.66CDPP +Φ-OTDR system based on uwFBG2019Eliminate polarization fading
    ref.141Wiener filtering technology2012Reduce phase noise
    ref.16Statistics calculating method20156 dB SNR achievement by reducing polarization-dependent noise
    ref.17Auxiliary weak reflection points in fiber202060 dB SNR achievement by compensating polarization-dependent noise
    ref.49Laser frequency sweep + cross-correlation calculation2015Suppress the influence of LSFD
    ref.51A twice differential method2019The signal fluctuation induced by LSFD is decreased by more than 13 dB.
    ref.52An auxiliary MZI interferometer2019The low frequency noise is reduced by 10 dB
    ref.712D-ED20138.4 dB SNR by processing various noises together
    ref.142A new positioning method based on power spectrum analysis201419.4 dB SNR by processing various noises together
    ref.722D-ABLF2017>14 dB SNR improvement by processing various noises together
    ref.143ATMF2017>10 dB SNR achievement by processing various noises together
    ref.144Curvelet denoising20178 dB SNR achievement by processing various noises together
    ref.70EMD20172.74 dB SNR improvement by processing various noises together
    ref.145Multi-scale matched filtering20196 dB SNR improvement by processing various noises together
    ref.146A signal processing method based on CS201834.39 dB SNR by processing various noises together
    Table 0. Research progress on improving the SNR in Ф-OTDR systems
    ReferenceMethodYearSensing distance
    ref.122EDFA200325 km
    ref.123First-order bidirectional Raman amplification200962 km@100 m SR
    ref.124Second-order Raman amplification2014125 km@10 m SR
    ref.57First-order bidirectional Raman amplification + heterodyne detection2014131.5km@8 m SR
    ref.54Brillouin amplification + heterodyne detection2014124 km@10 m SR
    ref.125First-order Raman amplification + second-order Raman amplification + Brillouin amplification2014175 km@25 m SR
    ref.126B-EDFA2016123 km@8 m SR
    ref.127RP-EDFA201775 km
    ref.128Non-balanced optical repeaters2018150 km@20 m SR
    ref.129Long pulse + balanced amplified detector + heterodyne detection201560 km@6.8 m SR
    ref.130Cascaded AOMs + optimizing system components201994.8 km@10 m SR
    Table 0. Research progress on improving sensing distance in Ф-OTDR systems.
    ReferenceFeature extraction methodClassification methodsYearFeature extraction domainTypes of intrusion events
    ref.164Level crossing ratethreshold-based decision tree2014Time-domainClimbing up the wall + kicking at the wall + watering on the fiber
    ref.165SSABP ANN2014Time-domainSound interferences + hand perturbation
    ref.166Average and variance of the correlation coefficientsthreshold-based decision tree2017Time-domainJogging + digging
    ref.104SAKthreshold-based decision tree2018Time-domainPencil-break + digging
    ref.142Total energy of each sampling pointthreshold-based decision tree2014Frequency-domainKnocking on the fence with a steel spanner
    ref.167Energy information entropythreshold-based decision tree2015Frequency-domainRaindrop + construction machine + train + car
    ref.74The total energy + the ratio of the low-band energy to the total energy + the ratio of the peak amplitude to the average value of the spectrumSVM2015Frequency-domainA stable state + walking on the lawn while the fence is exposed to the win + shaking the fence + walking on the lawn + vibration exciter
    ref.73The sum of the normalized coefficients of the 10 frequency bandsSVM2016Frequency-domainTrain tracking
    ref.68WT2012Time-frequency domainPZT vibration
    ref.168WDthreshold-based decision tree2013time-frequency domainPersonal intrusion + hand clapping interferences
    ref.169WPD2014Time-frequency domainPZT vibration
    ref.102STFTGMM2016Time-frequency domainBig excavator + small excavator + pneumatic hammer + plate compactor
    ref.69HHT2014Time-frequency domainPZT vibration
    ref.171MFCCCNN2017time-frequency domainHuman digging + pile driver ramming + air pick hitting + excavator scrapping + environmental noise
    ref.113Normalized sliding varianceThreshold-based decision tree2014Time-space domainTrain tracking
    ref.172Morphological featuresRVM2015Time-space domainWalking + digging + vehicle passing
    ref.173Level crossing rate + power spectrum analysisSVM2017time-domain + frequency-domainTaping + striking + shaking + crushing
    ref.174Time-frequency entropy + center-of-gravity frequencyPNN2018Time-domain features + time-frequency domain featuresA stable state + tapping + climbing
    Table 0. Research progress on event discrimination in Ф-OTDR systems.
    ReferenceMethodYearHigh frequency response
    ref.147MZI20133 MHz in 1064 m
    ref.148MZI + TDM20136.3 MHz in 1150 m
    ref.149MZI + WDM201650 MHz in 2.5 km
    ref.44A pulse pair with a frequency difference20142 times improvement
    ref.150TSMF201530 kHz in 3024 m
    ref.42A hybrid single-end-access MZI20171.2 MHz in 6.35 km
    ref.43DFI20181 MHz in 2.16 km
    ref.151FLI2020300 kHz in 4 km
    ref.152Sagnac interferometer + WDM20202.5 MHz in 4 km
    ref.47Double-pulse heterodyne detection201820 kHz in 10 km
    ref.153OFDM + a weak reflector array Φ-OTDR202025 kHz in 51 km
    ref.154ARS+NLFM201920 kHz in 50 km
    Table 0. Research progress on improving frequency response range in Ф-OTDR systems.
    ReferenceMethodYearSpatial resolution
    ref.6Heterodyne detection + moving average + moving difference20105 m
    ref.712D-ED20133 m
    ref.155HOC20195 m
    ref.27Two separate FBGs + MZI201750 cm
    ref.156Two Michelson interferometers + PGC algorithm20180.8 m
    ref.157Pulse compression201730 cm
    ref.158FSP20180.95 m
    ref.159Chirped pulses201910 times improvement
    Table 0. Research progress on improving spatial resolution in Ф-OTDR systems.
    Shuaiqi Liu, Feihong Yu, Rui Hong, Weijie Xu, Liyang Shao, Feng Wang. Advances in phase-sensitive optical time-domain reflectometry[J]. Opto-Electronic Advances, 2022, 5(3): 200078
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