[1] [1] LV A Q, LI J. On-line monitoring system of 35 kV 3-core submarine power cable based on -OTDR[J]. Sensors and Actuators, 2018, A273: 134-139.

[3] [3] JUAREZ J C, TAYLOR H F. Field test of a distributed fiber-optic intrusion sensor system for long perimeters[J]. Applied Optics, 2007, 46(11): 1968-1971.

[4] [4] SENSFELDER E, BURCK J, ACHE H J. Characterization of a fiber-optic system for the distributed measurement of leakages in tanks and pipelines[J]. Applied Spectroscopy, 2016, 52(10): 1283-1298.

[5] [5] CHAE K S, LEE S P, LEE C H, et al. Application and development trend of OTDRs[J]. Tunnel and Underground Space, 2011, 21(1): 1-10.

[6] [6] FUKURO A, TORIGOE T, MIZUGUCHI H, et al. Application of a new measuring method using an optical fiber strain sensor to an underground tunnel[J]. International Journal of Modern Physics, 2006, B20(25/27): 3692-3697.

[7] [7] WATKINS S E. Smart bridges with fiber-optic sensors[J]. IEEE Instrumentation & Measurement Magazine, 2003, 6(2): 25-30.

[8] [8] JIANG F, LU Z X, CAI F, et al. Low computational cost distributed acoustic sensing using analog I/Q demodulation[J]. Sensors, 2019, 19(17): 3753-3762.

[12] [12] YANG Ch, OH S K, YANG B, et al. Hybrid fuzzy multiple SVM classifier through feature fusion based on convolution neural networks and its practical applications[J]. Expert Systems With Applications, 2022, 202(15): 117392.

[13] [13] ALI J, ALDHAIFALLAH M, NISAR K S, et al. Regularized least squares twin SVM for multiclass classification[J]. Big Data Research, 2022, 27(28): 100295.

[16] [16] MAHMOUD S S, KATSIFOLIS J. Robust event classification for a fiber optic perimeter intrusion detection system using level crossing features and artificial neural networks[J]. Proceedings of the SPIE, 2010, 7677: 767708.

[17] [17] ZHU H, PAN C, SUN X H. Vibration pattern recognition and cla-ssification in OTDR based distributed optical-fiber vibration sensing system[J]. Smart Sensor Phenomena, Technology, Networks, and Systems Integration 2014, 9062: 906205.

[21] [21] CORTES C, VAPNIK V. Support-vector networks[J]. Machine Learning, 1995, 20(3): 273-297.