딥러닝 기반 광섬유 분포 음향·진동 계측기술을 활용한 장거리 외곽 침입감지 시스템 개발
Development of Long-perimeter Intrusion Detection System Aided by deep Learning-based Distributed Fiber-optic Acoustic·vibration Sensing Technology
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Distributed fiber-optic acoustic·vibration sensing technology is becoming increasingly popular in many industrial and academic areas such as in securing large edifices, exploring underground seismic activity, monitoring oil well/reservoir, etc. Long-range perimeter intrusion detection exemplifies an application that not only detects intrusion, but also pinpoints where it happens and recognizes kinds of threats made along the perimeter where a single fiber cable was installed. In this study, we developed a distributed fiber-optic sensing device that measures a distributed acoustic·vibration signature (pattern) for intrusion detection. In addition, we demontrate the proposed deep learning algorithm and how it classifies various intrusion events. We evaluated the sensing device and deep learning algorithm in a practical testbed setup. The evaluation results confirm that the developed system is a promising intrusion detection system for long-distance and seamless recognition requirements.
Abstract
Distributed fiber-optic acoustic·vibration sensing technology is becoming increasingly popular in many industrial and academic areas such as in securing large edifices, exploring underground seismic activity, monitoring oil well/reservoir, etc. Long-range perimeter intrusion detection exemplifies an application that not only detects intrusion, but also pinpoints where it happens and recognizes kinds of threats made along the perimeter where a single fiber cable was installed. In this study, we developed a distributed fiber-optic sensing device that measures a distributed acoustic·vibration signature (pattern) for intrusion detection. In addition, we demontrate the proposed deep learning algorithm and how it classifies various intrusion events. We evaluated the sensing device and deep learning algorithm in a practical testbed setup. The evaluation results confirm that the developed system is a promising intrusion detection system for long-distance and seamless recognition requirements.
참고문헌 (17)
- M. F. Bado, "A Review of Recent Distributed Optical Fiber Sensors Applications for Civil Engineering Structural Health Monitoring", Sens, 21(5), pp.1818(1)~1818(83) (2021)
- H. Wu, "Feature extraction and identification in distributed optical-fiber vibration sensing system for oil pipeline safety monitoring", Photonic Sens, 7(4), pp.305~310 (2017)
- D. Tan, "An oil and gas pipeline pre-warning system based on Φ-OTDR", Proc. Int. Conf. Opt. Fibre Sensors, pp.91578W(1)~91578W(8) (2014)
- A. Lv, "On-line monitoring system of 35 kV 3-core submarine power cable based on Φ-OTDR", Sens. Actuators A, Phys, 273, pp.134~139 (2018)
- T. Parker, "Distributed Acoustic Sensing - A New Tool for Seismic Applications", Proc. of 74th EAGE Conference and Exhibition, pp.cp-293-008~cp-293-008 (2012)
- L. Shiloh, "Fiber-optic distributed seismic sensing data generator and its application for training classification nets", Opt. Lett, 45(7), pp.1834~1837 (2020)
- Z Wang, "Novel railway-subgrade vibration monitoring technology using phase-sensitive OTDR", 25th Optical Fiber Sensors Conference (OFS), pp.1~4 (2017)
- C. Du, "A review of railway infrastructure monitoring using fiber optic sensors", Sensors and Actuators A-physical, 303, pp.111728(1)~111728(36) (2020)
- Z. Li, "Fiber distributed acoustic sensing using convolutional long shortterm memory network : a field test on high-speed railway intrusion detection", Opt. Express, 28(3), pp.2925~2938 (2020)
- J. C. Juarez, "Field test of a distributed fiber-optic intrusion sensor system for long perimeters", Appl. Opt, 46(11), pp.1968~1971 (2007)
- F. Tanimola, "Distributed fibre optic sensors for pipeline protection", J. Nat. Gas. Sci. Eng, 1(4–5), pp.134~143 (2009)
- A. Owen, "OptaSense : Fibre Optic Distributed Acoustic Sensing for Border Monitoring", 2012 Eur. Intell. Secur. Inform. Conf, pp.362~364 (2012)
- A. V. Makarenko, "Deep learning algorithms for signal recognition in long perimeter monitoring distributed fiber optic sensors", 2016 IEEE 26th Int. Workshop on Mach. Learn. Signal Process. (MLSP), pp.1~6 (2016)
- M. Aktas, "Deep learning based multi-threat classification for phaseOTDR fiber optic distributed acoustic sensing applications", Proc. SPIE 10208, Fiber Optic Sens. Appl. XIV, 10208 (2017)
- C. Xu, "Pattern recognition based on time-frequency analysis and convolutional neural networks for vibrational events in φ-OTDR", Opt. Eng, 57(1), pp.016103(1)~016103(7) (2018)
- Y. Shi, "An Event Recognition Method for Φ-OTDR Sensing System Based on Deep Learning", Sens, 19(15), pp.3421(1)~3421(9) (2019)
- L. Shiloh, "Efficient Processing of Distributed Acoustic Sensing Data Using a Deep Learning Approach", J. Lightwave Technol, 37(18), pp.4755~4762 (2019)