Abstract
High sensitivity of a distributed optical-fiber vibration sensing (DOVS) system based on the phase-sensitivity optical time domain reflectometry (Φ-OTDR) technology also brings in high nuisance alarm rates (NARs) in real applications. In this paper, feature extraction methods of wavelet decomposition (WD) and wavelet packet decomposition (WPD) are comparatively studied for three typical field testing signals, and an artificial neural network (ANN) is built for the event identification. The comparison results prove that the WPD performs a little better than the WD for the DOVS signal analysis and identification in oil pipeline safety monitoring. The identification rate can be improved up to 94.4%, and the nuisance alarm rate can be effectively controlled as low as 5.6% for the identification network with the wavelet packet energy distribution features.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Y. J. Rao, J. Luo, Z,_L. Ran, J. F. Yue, X. D. Luo, and Z. Zhou, “Long-distance fiber-optic Φ-OTDR intrusion sensing system,” SPIE, 2009, 7503: 1–4.
W. T. Lin, S. Q. Lou, and S. Liang, “Fiber-optic distributed vibration sensor for pipeline pre-alarm,” Applied Mechanics and Materials, 2014, 684: 235–239.
H. J. Wu, Y. Qian, H. Y. Li, S. K. Xiao, Z. Z. Fu, and Y. J. Rao, “Safety monitoring of long distance power transmission cables and oil pipelines with OTDR technology,” in Proceeding of Laser and Electro-optics (CLEO), San Jose, CA, USA, 2015, pp: 1–2.
F. Peng, H. Wu, X. H. Jia, and Z. P. Peng, “Ultra-long high-sensitivity Φ-OTDR for high spatial resolution intrusion detection of pipelines,” Optics Express, 2014, 22(11): 13804–13810.
H. J. Wu, X. Y. Li, Z. P. Peng, and Y. J. Rao, “A novel intrusion signal processing method for phase-sensitive optical time-domain reflectometry (Φ-OTDR),” SPIE, 2014, 9157: 9157O-1–9157O-4.
H. J. Wu, S. K. Xiao, X. Y. Li, Z. N. Wang, J. W. Xu, and Y. J. Rao, “Separation and determination of the disturbing signals in phase-sensitive optical time domain reflectometry (Φ-OTDR),” Journal of Lightwave Technology, 2015, 33(15): 3156–3162.
Z. G. Qin, L. Chen, and X. Y. Bao, “Wavelet denoising method for improving detection performance of distributed vibration sensor,” IEEE Photonics Technology Letters, 2012, 24(7): 542–544.
Q. Li, C. X. Zhang, and C. S. Li, “Fiber-optic distributed sensor based on phase-sensitive OTDR and wavelet packet transform for multiple disturbances location,” Optik, 2014, 125(24): 7235–7238.
H. M. Yue, B. Zhang, Y. X. Wu, B. Y. Zhao, J. F. Li, J. H. Ou, 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, 2015, 54(4): 047101-1–047101-6.
Z. Y. Wang, Z. Q. Pan, Q. Y. Qing, B. Lu, Z. J. Fang, H. W. Cai, et al., “Novel distributed passive vehicle tracking technology using phase sensitive optical time domain reflectometer,” Chinese Optics Letters, 2015, 13(10): 30–34.
B. Asgarian, V. Aghaeidoost, and H. R. Shokrgozar, “Damage detection of jacket type offshore platforms using rate of signal energy using wavelet packet transform,” Marine Structures, 2015, 45: 1–21.
A. B. Meng, J. F. Ge, H. Yin, and S. Z. Chen, “Wind speed forecasting based on wavelet packet decomposition and artificial neural networks trained by crisscross optimization algorithm,” Energy Conversion and Management, 2016, 114: 75–88.
Acknowledgement
The authors gratefully acknowledge the supports provided for this research by Youth Foundation (Grant No. 61301275), Major Instrument Special Program (Grant No. 41527805), the Major Program (Grant No. 61290312) of the National Science Foundation of China (NSFC), and the fund of State Grid Corporation of China: Research on distributed multi-parameter sensing and measurement control technology for electric power optical fiber communication networks (Grant No. 5455HT160014). This work is also supported by Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT, IRT1218) and the 111 Project (B14039).
Author information
Authors and Affiliations
Corresponding author
Additional information
This article is published with open access at Springerlink.com
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
About this article
Cite this article
Wu, H., Qian, Y., Zhang, W. et al. Feature extraction and identification in distributed optical-fiber vibration sensing system for oil pipeline safety monitoring. Photonic Sens 7, 305–310 (2017). https://doi.org/10.1007/s13320-017-0360-1
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13320-017-0360-1