A computerized system for Monitoring and informing about any unauthorized drilling operations near the cables.

Selah ABUFANA; Emad ZARGOUN

doi:10.58916/jhas.v8i3.115

Authors

Selah ABUFANA Computer Department College of science Bani waleed University Bani waleed/ Libya Author
Emad ZARGOUN Computer Department College of science Bani waleed University Bani waleed/ Libya Author

DOI:

https://doi.org/10.58916/jhas.v8i3.115

Keywords:

Acoustic sensing, DAS systems, sensing, monitoring system

Abstract

The biggest challenge is to protect the cables in cities and villages from random excavations, as the protection of these cables by traditional methods such as concrete and some cement stones is not sufficient. It has become necessary to search for effective and alternative protection techniques that can protect the cables. In this paper, a novel method is proposed to design a drill monitoring system for early warning using fiber optic distributed acoustic sensing systems (DAS) based on phase OTDR. The proposed method has three stages. The first stage is to use buried fiber optic cable as a sensing system to detect any activity such as drilling or digging near the cable. The second stage is the processing system; in this stage, the sensed signal is de-noised using a wavelet transform, and then the difference is used for high pass filtering. This phase includes the autocorrelation to improve the interferometric visibility of the movements or threats near the goal area via a fiber optic cable. Moreover, the correlated signal power is computed and sent to the test and comparison stages. In the last stage, all signals are compared with a predefined threshold; if the average exceeds the threshold, the discrete signal is considered to be high, and there is drilling near cables; otherwise, the signals are considered to be undesired signals. Different types of activities were used at different SNR levels to assess the effects of the proposed method on detection performance. The results show the effectiveness of the used system for early drilling detection to protect the cables.

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References

D. Hill, Distributed Acoustic Sensing (DAS): Theory and Applications, pp. 4,5, 2015.

Y. Liu et al., Distributed fiber optic sensors for vibration detection, Sensors, vol. 16, no. 8, 1164, 2016.

Abufana. S. A et al., Variational mode decomposition based threat classification for fiber optic distributed acoustic sensing, IEEE Access,2020.8:100152-100158J.

H. Yue et al., Simultaneous and signal-to-noise ratio enhancement extraction of vibration location and frequency information in phase sensitive optical time domain reflectometry distributed sensing system, Optical Engineering, vol. 54, no. 4, 047101, Apr. 2015

F. Peng et al., Real-time position and speed monitoring of trains using phase-sensitive OTDR, IEEE Photonics Technology Letters, vol. 26, no. 20, pp. 20552057, Oct. 2014.

Z. Wang et al., Novel Railway-Subgrade Vibration Monitoring Technology Using Phase-Sensitive OTDR, in Proc. SPIE 10323,25th International Conference on Optical Fiber Sensors, Jeju, SouthKorea, 2017.

J. C. Juarez, E. W. Maier, and H. F. Taylor, Distributed fiber-optic intrusion sensor system, Journal of Lightwave Technology, vol. 23,no. 6, pp. 20812087, June 2005.

H. Liu et al., Traffic flow detection using distributed fiber optic acoustic sensing, IEEE Access, vol. 7, pp. 6896868980, 2018.

F. Peng et al., Ultra-long high-sensitivity-OTDR for high spatial resolution intrusion detection of pipelines, Optic Express, vol. 22, no.11, pp. 1380413810, Jun. 2014.

H. Wu et al., Separation and determination of the disturbing signals in phase-sensitive optical time domain reflectometry (Φ-OTDR),”Journal of Lightwave Technology, vol. 33, no. 15, pp. 3156–3162,Aug. 2015.

I. Olcer, I. and A. Oncu, “Adaptive temporal matched filtering for noise suppression in fiber optic distributed acoustic sensing, Sensors,vol. 17, no. 6, 1288, 2017.

Z. Qin, L. Chen, and X. Bao, Wavelet de-noising method for improving detection performance of distributed vibration sensor,.IEEE Photonics Technology Letters, vol. 24, no. 7, pp. 542544, Apr.2012.

M. Aktaş et al., “Deep learning based multi-threat classification for phase-OTDR fiber optic distributed acoustic sensing applications,” in Proc. SPIE 10208, Fiber Optic Sensors and Applications XIV,Anaheim, California, United States, 2017.

A. Makarenko.“Deep learning algorithms for signal recognition in long perimeter monitoring distributed fiber optic sensors” 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2016.

Y. Muanenda.“Recent advances in distributed acoustic sensing based on phase-sensitive optical time domain reflectometry” Journal of Sensors 2018 (2018).‏

P. Kumar and K. Preetam. “DCT based OFDM for underwater acoustic communication. ” 2012 1st International Conference on Recent Advances in Information Technology (RAIT). IEEE, 2012.‏