• Opto-Electronic Engineering
  • Vol. 48, Issue 3, 200254 (2021)
Zhang Yongkang, Shang Ying, Wang Chen, Zhao Wen?an, Li Chang, Cao Bing, and Wang Chang*
Author Affiliations
  • [in Chinese]
  • show less
    DOI: 10.12086/oee.2021.200254 Cite this Article
    Zhang Yongkang, Shang Ying, Wang Chen, Zhao Wen?an, Li Chang, Cao Bing, Wang Chang. Detection and recognition of distributed optical fiber intrusion signal[J]. Opto-Electronic Engineering, 2021, 48(3): 200254 Copy Citation Text show less
    References

    [1] Juarez J C, Maier E W, Choi K N, et al. Distributed fiber-optic intrusion sensor system[J]. J Light Technol, 2005, 23(6): 2081–2087.

    [2] Pan Z Q, Liang K Z, Ye Q, et al. Phase-sensitive OTDR system based on digital coherent detection[J]. Proc SPIE, 2011, 8311: 83110S.

    [3] Juarez J C, Taylor H F. Field test of a distributed fiber-optic intrusion sensor system for long perimeters[J]. Appl Opt, 2007, 46(11): 1968–1971.

    [4] Lindsey N J, Martin E R, Dreger D S, et al. Fiber-optic network observations of earthquake wavefields[J]. Geophys Res Lett, 2017, 44(23): 11792–11799.

    [5] Cedilnik G, Hunt R, Lees G. Advances in train and rail monitoring with DAS[C]//Proceedings of the 26th International Conference on Optical Fiber Sensors, 2018: ThE35.

    [6] Wu H J, Chen J P, Liu X R, et al. One-dimensional CNN-based intelligent recognition of vibrations in pipeline monitoring with DAS[J]. J Light Technol, 2019, 37(17): 4359–4366.

    [7] Johannessen K, Drakeley B, Farhadiroushan M. Distributed acoustic sensing-a new way of listening to your well/reservoir[C]//SPE Intelligent Energy International, Utrecht, the Netherlands, 2012: 149602.

    [8] Bao X Y, Zhou D P, Baker C, et al. Recent development in the distributed fiber optic acoustic and ultrasonic detection[J]. J Light Technol, 2017, 35(16): 3256–3267.

    [9] Muanenda Y. Recent advances in distributed acoustic sensing based on phase-sensitive optical time domain reflectometry[J]. J Sens, 2018, 2018: 3897873.

    [10] Adeel M, Shang C, Zhu K, et al. Nuisance alarm reduction: using a correlation based algorithm above differential signals in direct detected phase-OTDR systems[J]. Opt Express, 2019, 27(5): 7685–7698.

    [12] Mahmoud S S, Katsifolis J. Elimination of rain-induced nuisance alarms in distributed fiber optic perimeter intrusion detection systems[J]. Proc SPIE, 2009, 7316: 731604.

    [20] Cao C, Fan X Y, Liu Q W, et al. Practical pattern recognition system for distributed optical fiber intrusion monitoring system based on phase-sensitive coherent OTDR[C]//Asia Communications and Photonics Conference 2015, 2015: ASu2A.145.

    [24] Tejedor J, Martins H F, Piote D, et al. Toward prevention of pipeline integrity threats using a smart fiber-optic surveillance system[J]. J Light Technol, 2016, 34(19): 4445–4453.

    [25] Tejedor J, Macias-Guarasa J, Martins H F, et al. A novel fiber optic based surveillance system for prevention of pipeline integrity threats[J]. Sensors, 2017, 17(2): 355.

    [28] Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proc Math Phys Eng Sci, 1998, 454(1971): 903–995.

    [29] Liu K, Tian M, Liu T G, et al. A high-efficiency multiple events discrimination method in optical fiber perimeter security system[J]. J Light Technol, 2015, 33(23): 4885–4890.

    [35] Wu H J, Xiao S K, Li X Y, et al. Separation and determination of the disturbing signals in phase-sensitive optical time domain reflectometry (Φ-OTDR)[J]. J Light Technol, 2015, 33(15): 3156–3162.

    [38] Wu H J, Qian Y, Zhang W, et al. Feature extraction and identification in distributed optical-fiber vibration sensing system for oil pipeline safety monitoring[J]. Photonic Sens, 2017, 7(4): 305–310.

    [40] Sun Q, Feng H, Yan X Y, et al. Recognition of a phase-sensitivity OTDR sensing system based on morphologic feature extraction[J]. Sensors, 2015, 15(7): 15179–15197.

    [41] Aslangul S A. Detecting tunnels for border security based on fiber optical distributed acoustic sensor data using DBSCAN[C]//Proceedings of the 9th International Conference on Sensor Networks, 2020: 78–84.

    [42] Cortes C, Vapnik V. Support-vector networks[J]. Mach Learn, 1995, 20(3): 273–297.

    [43] Qi X X, Ji J W, Han X W, et al. An Approach of passive vehicle type recognition by acoustic signal based on SVM[C]//Proceedings of the 2009 Third International Conference on Genetic and Evolutionary Computing, 2009: 545–548.

    [44] King D, Lyons W B, Flanagan C, et al. A multipoint optical fibre sensor system for use in process water systems based on artificial neural network pattern recognition techniques[J]. Sens Actuator A Phys, 2004, 115(2–3): 293–302.

    [45] Lewis E, Sheridan C, O’Farrell M, et al. Principal component analysis and artificial neural network based approach to analysing optical fibre sensors signals[J]. Sens Actuator A Phys, 2007, 136(1): 28–38.

    [47] Tipping M E. The relevance vector machine[C]//Advances in Neural Information Processing Systems, 2000: 652–658.

    [50] Rumelhart D E, Hinton G E, Williams R J. Learning internal representations by error propagation[M]//Parallel Distributed Processing: Explorations in the Microstructure Of Cognition, Vol. 1: Foundations. Cambridge: MIT Press, 1986: 318–362.

    [54] Aktas M, Akgun T, Demircin M U, et al. Deep learning based threat classification in distributed acoustic sensing systems[C]//Proceedings of the 2017 25th Signal Processing and Communications Applications Conference (SIU), 2017.

    [55] Xu C J, Guan J J, Bao M, et al. Pattern recognition based on time-frequency analysis and convolutional neural networks for vibrational events in φ-OTDR[J]. Opt Eng, 2018, 57(1): 016103.

    [56] Shi Y, Wang Y Y, Zhao L, et al. An event recognition method for Φ-OTDR sensing system based on deep learning[J]. Sensors (Basel), 2019, 19(15): 3421.

    [58] Goodfellow I J, Pouget-Abadie J, Mirza M, et al. Generative adversarial nets[C]//Proceedings of the 27th International Conference on Neural Information Processing Systems, 2014: 2672–2680.

    [59] Shiloh L, Eyal A, Giryes R. Deep learning approach for processing fiber-optic DAS seismic data[C]//Proceedings of the 26th International Conference on Optical Fiber Sensors, 2018: ThE22.

    [60] Li W, Zeng Z Q, Qu H Q, et al. A novel fiber intrusion signal recognition method for ofps based on SCN with dropout[J]. J Light Technol, 2019, 37(20): 5221–5230.

    [61] Wang Z Y, Zheng H R, Li L C, et al. Practical multi-class event classification approach for distributed vibration sensing using deep dual path network[J]. Opt Express, 2019, 27(17): 23682–23692.

    [62] Chen X, Xu C J. Disturbance pattern recognition based on an ALSTM in a long-distance φ-OTDR sensing system[J]. Microw Opt Technol Lett, 2020, 62(1): 168–175.

    [63] Li Z Q, Zhang J W, Wang M N, et al. Fiber distributed acoustic sensing using convolutional long short-term memory network: a field test on high-speed railway intrusion detection[J]. Opt Express, 2020, 28(3): 2925–2938.

    Zhang Yongkang, Shang Ying, Wang Chen, Zhao Wen?an, Li Chang, Cao Bing, Wang Chang. Detection and recognition of distributed optical fiber intrusion signal[J]. Opto-Electronic Engineering, 2021, 48(3): 200254
    Download Citation