Recent Advances in Phase-Sensitive Optical Time Domain Reflectometry (Ф-OTDR)

Abstract

Phase-sensitive optical time domain reflectometry (Ф-OTDR) is an effective way to detect vibrations and acoustic waves with high sensitivity, by interrogating coherent Rayleigh backscattering light in sensing fiber. In particular, fiber-optic distributed acoustic sensing (DAS) based on the Ф-OTDR with phase demodulation has been extensively studied and widely used in intrusion detection, borehole seismic acquisition, structure health monitoring, etc., in recent years, with superior advantages such as long sensing range, fast response speed, wide sensing bandwidth, low operation cost and long service lifetime. Significant advances in research and development (R&D) of Ф-OTDR have been made since 2014. In this review, we present a historical review of Ф-OTDR and then summarize the recent progress of Ф-OTDR in the Fiber Optics Research Center (FORC) at University of Electronic Science and Technology of China (UESTC), which is the first group to carry out R&D of Ф-OTDR and invent ultra-sensitive DAS (uDAS) seismometer in China which is elected as one of the ten most significant technology advances of PetroChina in 2019. It can be seen that the Ф-OTDR/DAS technology is currently under its rapid development stage and would reach its climax in the next 5 years.

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Acknowledgment

The authors would like to thank all of the members in the FORC at UESTC for their hard work and important contributions to this work. This work was funded by the Natural Science Foundation of China (Grant Nos. 41527805 and 61635005) and the 111 Poject (Grant No. B14039).

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Correspondence to Yunjiang Rao or Zinan Wang.

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Rao, Y., Wang, Z., Wu, H. et al. Recent Advances in Phase-Sensitive Optical Time Domain Reflectometry (Ф-OTDR). Photonic Sens 11, 1–30 (2021). https://doi.org/10.1007/s13320-021-0619-4

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Keywords

  • Distributed optical fiber sensing
  • phase-sensitive optical time domain reflectometry
  • Rayleigh backscattering
  • optical phase demodulation
  • distributed acoustic sensing
  • long-distance sensing
  • artificial intelligence