RVFL-Based Optical Fiber Intrusion Signal Recognition With Multi-Level Wavelet Decomposition as Feature

Yanping WANG; Dianjun GONG; Liping PANG; Dan YANG

doi:10.1007/s13320-018-0496-7

[1] W. Q. Lu, W. Liang, L. B. Zhang, and W. Liu, “A novel noise reduction method applied in negative pressure wave for pipeline leakage localization,” Process Safety and Environmental Protection, 2016, 104(part A): 142-149.

[2] K. Jing and Z. H. Zou, “Time prediction model for pipeline leakage based on grey relational analysis,” Physics Procedia, 2012, 25(2): 2019-2024.

[3] W. Liang, L. L. Lu, and L. B. Zhang, “Coupling relations and early-warning for ‘equipment chain’ in long-distance pipeline,” Mechanical Systems and Signal Processing, 2013, 41(1/2): 335-347.

[4] X. Wang and M. S. Ghidaoui, “Identification of multiple leaks in pipeline: linearized model, maximum likelihood, and super-resolution localization,” Mechanical Systems and Signal Processing, 2018, 107: 529-548.

[5] M. Zadkarami, M. Shahbazian, and K. Salahshoor, “Pipeline leakage detection and isolation: an integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN),” Journal of Loss Prevention in the Process Industries, 2016, 43: 479-487.

[6] G. Allwood, G. Wild, and S. Hinckley, “Optical fiber sensors in physical intrusion detection systems: a review,” IEEE Sensors Journal, 2016, 16(14): 5497-5509.

[7] Y. Zhan, Q. Yu, K. Wang, F. Yang, Y. Kong, and X. Zhao, “A high performance distributed sensor system with multi-intrusions simultaneous detection capability based on phase sensitive OTDR,” Opto-Electronics Review, 2015, 23(3): 187-194.

[8] Y. Shi, H. Feng, Y. An, X. Geng, and Z. M. Zeng, “Research on wavelet analysis for pipeline pre-warning system based on phase-sensitive optical time domain reflectometry,” in Proceeding of IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Besancon, France, 2014, pp. 1177-1182.

[9] H. Q. Qu, T. Zheng, F. K. Bi, and L. P. Pang, “A vibration detection method for optical fiber pre-warning system,” IET Signal Processing, 2016, 10(6): 692-698.

[10] Z. Z. Qiu, T. Zheng, H. Q. Qu, and L. P. Pang, “A new detection method based on CFAR and DE for OFPS,” Photonic Sensors, 2016, 6(3): 261-267.

[11] N. Lu, B. W. An, and Y. L. Li, “Signal recognition algorithm of fiber-optic security system based on time-domain features,” Transducer and Microsystem Technologies, 2017, 36(4): 150-152.

[12] L. Zhu, Z. M. Zeng, J. C. Zhang, and S. J. Jin, “Feature extraction of vibration signal detected by optical fiber along crude oil pipeline and forewarning system based on ICA,” in Proceeding of International Workshop on Intelligent Systems and Applications, Wuhan, China, 2009, pp. 1-4.

[13] H. J. Wu, Z. N. Wang, F. Peng, Z. P. Peng, X. Y. Li, Y. Wu, et al., “Field test of a fully distributed fiber optic intrusion detection system for long-distance security monitoring of national borderline,” Society of Photo-Optical Instrumentation Engineers, 2014, 9157: 915790-915790-4.

[14] A. Klar and R. Linker, “Feasibility study of the automated detection and localization of underground tunnel excavation using Brillouin optical time domain reflectometer,” SPIE, 2009, 7316(5): 433-443.

[15] Y. X. Lv, S. X Sun, and X. H. Gu, “Battlefield acoustic target classification and recognition based on EMD and power ratio,” Journal of Vibration and Shock, 2008, 27(11): 51-55.

[16] Y. Lu, Z. K. Han, and Y. Chen, “FFT narrow band filtering method based on energy-ratio pretreatment,” Journal of Southeast University (Natural Science Edition), 2010, 40(5): 948-951.