Abstract

An ultra-long phase-sensitive optical time domain reflectometry (Φ-OTDR) that can achieve high-sensitivity intrusion detection over 131.5km fiber with high spatial resolution of 8m is presented, which is the longest Φ-OTDR reported to date, to the best of our knowledge. It is found that the combination of distributed Raman amplification with heterodyne detection can extend the sensing distance and enhances the sensitivity substantially, leading to the realization of ultra-long Φ-OTDR with high sensitivity and spatial resolution. Furthermore, the feasibility of applying such an ultra-long Φ-OTDR to pipeline security monitoring is demonstrated and the features of intrusion signal can be extracted with improved SNR by using the wavelet detrending/denoising method proposed.

© 2014 Optical Society of America

1. Introduction

Compared with other optical fiber intrusion sensors, phase-sensitive optical time domain reflectometer (Ф-OTDR) has great potential for realization of long-distance intrusion detection due to its high sensitivity, fully distributed manner, relatively low cost, accurate localization and simultaneous multi-point intrusion detection ability, et al. [111]. In particular, Ф-OTDR is ideal for applications where ultra-long-distance security monitoring is needed, such as oil/gas pipelines, electrical cables, military bases, national borders, et al, if the sensing distance of Ф-OTDR could be extended to >100km.

Valuable work has been carried out to improve the sensing performance of Ф-OTDR. But achieving a Ф-OTDR with ultra-long distance, high spatial resolution (SR) and high sensitivity simultaneously remains as a longstanding challenge. The first challenge is that the sensing distance of EDFA-based Ф-OTDR is limited by the peak power of probe pulses in order to suppress undesired nonlinear effects in the fiber, like modulation instability [2]. The trade-off among signal-to-noise-ratio (SNR), SR and sensing range always exists in Ф-OTDR [37]. We used 1st-order bidirectional Raman amplification (BRA) in Ф-OTDR and extended its sensing range to 62km with 100m SR previously [7, 8]. However, due to the use of direct detection, the sensing performance of this system was not further improved. In a recent work by Martins et al used optical switch to greatly decrease the intra-band coherent noise existing in the 1-st Raman-amplification-based Φ-OTDR and suppress the ASE noise by the balanced detection of two adjacent channels, which extended the sensing range significantly [9]. But if the sensing range is over 120km, RS in rather long range (at least 30km) cannot be amplified sufficiently in bi-directional 1-st order assisted Φ-OTDR. In these areas, the detection SNR is not enough if direct detection is used, causing the interference fringe was not clear. Y. Lu et al introduce coherent detection to Φ-OTDR [10]. The SNR of sensing signal can be improved greatly by mixing the RS with the local oscillator and filtering out the ASE noise from the mixed signal. The ability of frequency response was promoted when the detection SNR was enhanced greatly.

Another challenge is signal processing for practical applications, such as security monitoring of pipelines. Firstly, the response frequency of long distance Ф-OTDR is limited by relatively low trigger frequency of the probe pulses. Therefore, the average number of the Rayleigh scattering (RS) curves, which determines the response frequency, has to be deliberated to meet the needs of practical applications. Secondly, we should extract the intrusion signal features effectively from the time series in low system response frequency. Discrete-time wavelet transform shrinkage has good effect in denoising for short-distance Φ-OTDR with EDFA amplification [11], but the shrinkage strategy is not suitable for detecting the low frequency disturbance signal generated in long distance Φ-OTDR. In addition, the BRA may introduce additional intensity noise while amplifying the probe pulses, so the background noise between the long-distance Φ-OTDR and short-distance Φ-OTDR would be different.

In this paper, we present an ultra-long high-sensitivity Φ-OTDR with 8m SR over 131.5km sensing distance, indicating a breakthrough to promote Φ-OTDR towards ultra-long-distance practical applications, especially for pipeline security monitoring. The combination of heterodyne detection and BRA can form a new solution of realizing ultra-long Φ-OTDR with high sensitivity due to the fact that the BRA can compensate the losses of probe pulses and RS light with lower noise figure and more uniform gain distribution than EDFA. And the heterodyne detection overcomes the shortcoming of Raman amplification by filtering the ASE noise effectively by high power Raman pump. With optimized power combination of the Raman pump and probe pulses, the probe pulses can generate strong backscattering signal and keep high temporal coherence over the whole fiber link simultaneously. Furthermore, a wavelet detrending/denoising is proposed for the application in pipeline security monitoring. High SNR intrusion signal along the whole sensing distance is obtained. The vibration test demonstrated that the system is able to detect weak vibration over 131.5km sensing range with high sensitivity (SNR up to 21.5dB when the frequency is 375Hz and the electrostriction displacement is <3μm). Also, the time domain features of intrusion signal on pipelines are analyzed and extracted effectively. The experimental results show that it is feasible to achieve high-sensitivity intrusion detection for pipeline security monitoring over ultra-long distance with such a Φ-OTDR system.

2. Experimental setup

The schematic diagram of Φ-OTDR based on 1st-order BRA and heterodyne detection is shown in Fig. 1. A narrow line width (~3kHz) semiconductor laser at 1550nm with maximum power of 12dBm is used. This laser has a very small frequency drift (<1 MHz/min), which is important for achieving interference stability. The laser is divided into two portions by 50:50 coupler 1. One portion is modulated to pulse with 770Hz repetition rate and 80ns pulse width. 200MHz frequency shift is induced by using an acoustic-optic modulator (AOM). Then the pulse light is amplified by an EDFA and passed to band pass filter (BPF) to suppress the amplified spontaneous emission noise generated by EDFA. Then the pulse light launched into the fiber via a circulator. A Raman fiber laser with central wavelength of 1455nm is used as the Raman pump. The probe pulses are distributed amplified by bidirectional Raman pumps, generating RS light along the fiber. Another portion of light split by coupler 1 is used as the local oscillator with a polarization controller (PC). The local oscillator light is first adjusted by the variable optical attenuator (VOA) and then mixed with the RS signal by coupler 2. Then the beat light is detected by a balanced photodetector with 350MHz bandwidth and analyzed by an electronic spectrum analyzer (ESA). The RS curves are sampled by an A/D card with 50MSample/s. Finally, the sampled signal is processed by a computer in real-time.

 

Fig. 1 Experimental setup of Φ-OTDR system with 1-st BRA and heterodyne detection.

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3. Experiment results

3.1 Power optimization of probe pulse and Raman pump

To realize an ultra-long distance Φ-OTDR with high and uniform sensitivity distribution along the whole fiber, the power optimization of probe pulse and Raman pump is essential. The first factor should be considered is stimulated Brillouin scattering (SBS). In the experiment, due to ultra-narrow linewidth laser is used, SBS threshold is lower compared with wide linewidth laser [12]. When the power of Raman pump PR = 0 and the average power of probe pulse Pp = −19.4dBm, the Brillouin Stokes light is rather obvious (in Fig. 2(a)). Due to the depletion of SBS, the probe pulse is rapid attenuated (in Fig. 2(b)).

 

Fig. 2 (a) The optical spectrum (observed at the output of BPF2) and (b) RS curve when PR = 0 and Pp = −19.4dBm.

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Considering the Raman gain for the probe pulse, to avoid SBS, the Pp should be set much lower than −20dBm to avoid SBS. However, when Pp is too weak, the RS has to go through much longer amplification length before it increases to a relative ideal level even when PR is quite large. As seen in Fig. 3(b), when Pp = −41.7dBm, the RS power is quite low over the whole fiber length. When PR is too high, the relatively high-level amplified spontaneous emission (ASE) generated by Raman pump will beat with RS, which causes the detected RS curves fluctuate considerably. As an example, when Pp = −36.3dBm and PR = 32.7dBm, the ASE noise level is rather high, which can be inferred by the detected noise level outside the fiber in Fig. 3(a).

 

Fig. 3 RS curves in different power combinations of probe pulses and Raman pump. The red lines are the simulated RS curves.

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When the PR and Pp are both set to the proper value, it is reasonable to ignore the ASE and other nonlinear effects in numerical simulation. In this condition, a uniform power distribution of RS curves is desired. The power distribution of RS curve can be simulated by the coupled equations between probe pulse and Raman pump [12].

dPPdz=gRPRPPαPPP
ξdPRdz=ωRωSgRPRPPαRPR
where P represents the optical power, g is the Raman gain, α is the attenuation coefficient, ω is the angular frequency of the light, the low indexes ‘R’, ‘P’ correspond to Raman pump and probe pulse, respectively. The parameter ξ takes values + 1 on forward pumping and −1 on backward-pumping case. PP(z) can be solved by Eqs. (1)-(2), the RS curve can be obtained by αBSPP(0)G(z)2Δz, where Δz is determined by the pulse width of probe pulse, αBS is Rayleigh scattering coefficients and G(z) is the net gain distribution, which is calculated by PP(z)/PP(0). The simulation parameters are set as following: αP = 0.2dB/km (@1550nm), αS = 0.24dB/km (@1455nm), gR = 1.62dB/(W∙km) and the Rayleigh scattering coefficients αSMF_BS = −42.3dB/km. The simulated RS curves are shown in Figs. 3(b)-3(d), which are basically in accordance with the experimental results.

When PR is too small, the probe pulse and RS cannot be amplified sufficiently, just as shown in Fig. 3(c). Compared with the other power combinations, when the Pp = −36.3dBm and PR = 31.5dBm, as shown in Fig. 3(d), the power of RS is kept at a comparatively high level and the interference is clear over the whole fiber. In this power combination, the noise level is very low, which can be evaluated by the detected noise level outside the fiber (the enlarged part of Fig. 3(d)). Some other power combinations may have the similar good effect or even better, but this power combination already meets the demands of vibration detection with high-sensitivity in 131.5km range.

3.2 Response frequency of ultra-long Φ-OTDR

Limited by the long trigger period, the maximum response frequency of long-distance Φ-OTDR is much lower than that of short distance Φ-OTDR. According to the Nyquist Sampling theorem, the maximum response frequency of Φ-OTDR fr can be expressed as fr = 1/(2∙TtNa), where Tt is the trigger period and Na is the average number. fr is only determined by Na when the limited Tt is determined by the distance of fiber. In the experiment, the trigger frequency of pulse is 770Hz, which matches the fiber length well. To test the maximum response frequency of the system, we set Na = 1 and applied the vibration generated by PZT cylinder to a 5m fiber at 97.51km. The system works in the optimized power parameter as shown in Fig. 3(d). The diameter of the PZT is 7cm and the dielectric layer is 0.5cm. Piezoelectric constant is 300pm/V. The total electrostriction displacement is ~3μm when the driven voltage is 3V. The driven signal applied to PZT cylinder is a sinusoidal wave, whose peak-peak voltage is 3V and frequencies are adjusted from 25Hz to 375Hz. The auto-spectrums of 97.51km when vibrations of different frequencies applied are shown in Fig. 4. The peak frequency of each spectrum is in good agreement with the frequency of the vibration applied and has high SNR, which shows that this system has good ability for high frequency response.

 

Fig. 4 Auto-spectrum of 97.51km when the driven signal with different frequencies are applied.

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Figure 5(a) shows the auto-power spectrum of vibration along the fiber when the frequency of vibration applied at 97.51km is 375Hz. From the Fig. 5(b), the SNR can reach up to 21.5dB though no denoising methods are applied and the spatial resolution is ~8m (the rising edge is 4 spatial points), which is coincidence with the pulse width of the probe pulse. Therefore, the maximum detection frequency of this system is 375Hz, which is close to the limit response frequency of this system.

 

Fig. 5 (a) Auto-power spectrum of vibration along the fiber when the vibration frequency at 97.51km is 375Hz. (b) Amplitude at 375Hz of each position. The sub graph in (b) is the enlarged part around 97.51km.

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3.3 Intrusion signal processing of pipeline

To test the sensing performance of the system, a 2.5m-long optical fiber cable located at 97.51km (where the interference signal is the weakest towards the far-end of fiber) is glued at the surface of a steel pipeline firmly in line, just as shown in Fig. 6(a).

 

Fig. 6 (a) Steel pipeline with optical fiber cable attached. (b) Original time series (blue line) and slowly varying noises (red line) when chiseling the pipe. (c) Extracted disturbance series when chiseling on the pipe. The red * represent the peak of the impulses generated by chiseling the pipe.

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Φ-OTDR for pipeline applications is mainly used for monitoring of human intrusions, like digging, whose repeat frequencies are generally <5Hz. For the application of intrusion monitoring of pipeline, we find that Na = 32 is reasonable because not only the system meets the response frequency need of real intrusion detection, but also the noise is suppressed partly. We chiseled the pipe for 10 times. The force point is ~15cm away from the cable. The vibration transmits from the pipe to the cable. The intrusion signal is recorded when we chisel the pipeline, just as the blue line shown in Fig. 6(b).

From Fig. 6(b), slowly varying noise with large amplitude and high-frequency noise with small amplitude noise are both mixed in the intrusion signal. The slowly varying noise is mainly generated from the slow change process of polarization of the input probe pulses. In the case of short distance Ф-OTDR for high-frequency vibration measurement, slowly varying noise can be ignored in short time width. But the disturbance frequency generated by artificial damage is mostly a little larger than slowly varying noise. Slowly varying noise cannot be reduced by simply optimizing the hardware system [10, 11]. And high-frequency noise comes from the instability of light source and the intensity noise transfers from Raman fiber laser, which also weakens the SNR dramatically.

Compared with the high-frequency noises and slowly varying noises, the disturbance signals are neither too detailed nor too approximated. And the useful signals cannot be extracted simply by frequency filtering. Utilizing the multi-resolution analysis of wavelet, the useful disturbance information can be extracted effectively after multi-scale wavelet decomposition, coefficients adjustment and wavelet reconstruction [13]. At first, the discrete wavelet transform is applied to the noisy intrusion signal and obtained the detail coefficients and the approximation coefficients. In this system, wavelet detrending and denoising are two coefficients adjustment methods to reduce the high-frequency noises and slowly varying noises, respectively. After wavelet detrending (set the approximation coefficients to 0 of certain level) is used, the low frequency random fluctuation noise is rejected. The slowly varying noises almost disappeared after wavelet detrending. Then we set the detailed coefficients smaller than the setting threshold to 0 and keep the values of the other coefficients, the high frequency noises are reduced greatly and the intrusion information is extracted. The extracted vibration signal is shown in the Fig. 6(c). The noise of vibration series when no intrusion is suppressed in ultra-low level and the intrusion information is well-preserved. By detecting the peaks of the extracted vibration series, the timing of the impulses generated by chiseling the pipe can be located precisely.

4. Conclusion

In this paper, we demonstrated an ultra-long high-sensitivity Φ-OTDR with high spatial resolution and the feasibility of applying such a Φ-OTDR to pipeline security monitoring. The combination of bidirectional Raman amplification, heterodyne detection and wavelet detrending/denoising signal processing ensure high optical SNR over whole 131.5km fiber with 8m SR, leading to the best Φ-OTDR system for intrusion detection purpose reported so far. Such an ultra-long high-sensitivity Φ-OTDR could find important applications where ultra-long distance security monitoring is essential, such as oil/gas pipelines, electrical cables, military bases, national borders, et al.

Acknowledgments

This work is supported by the National Nature Science Foundation of China (NSFC) under grants (61290312, 61205048), the PCSIRT (IRT1218), and the 111 Project (B14039).

References and links

1. H. F. Taylor and C. E. Lee, “Apparatus and method for fiber optic intrusion sensing,” U. S. Patent 5, 194 847, March 16, 1993.

2. H. F. Martins, S. Martin-Lopez, P. Corredera, P. Salgado, O. Frazão, and M. González-Herráez, “Modulation instability-induced fading in phase-sensitive optical time-domain reflectometry,” Opt. Lett. 38(6), 872–874 (2013). [CrossRef]   [PubMed]  

3. J. Park, W. Lee, and H. F. Taylor, “A fiber optic intrusion sensor with the configuration of an optical time domain reflectometer using coherent interference of Rayleigh backscattering,” Proc. SPIE 3555, 49–56 (1998). [CrossRef]  

4. K. N. Choi and H. F. Taylor, “Spectrally stable Er-fiber laser for application in phase-sensitive optical time-domain reflectrometry,” IEEE Photon. Technol. Lett. 15(3), 386–388 (2003). [CrossRef]  

5. J. C. Juarez, E. W. Maier, K. N. Choi, and H. F. Taylor, “Distributed fiber-optic intrusion sensor system,” J. Lightwave Technol. 23(6), 2081–2087 (2005). [CrossRef]  

6. H. F. Martins, S. Martin-Lopez, P. Corredera, M. L. Filograno, O. Frazao, and M. Gonzalez-Herraez, “Coherent noise reduction in high visibility phase-sensitive optical time domain reflectometer for distributed sensing of ultrasonic waves,” J. Lightwave Technol. 31(23), 3631–3637 (2013). [CrossRef]  

7. Y. J. Rao, “OFS research over the last 10 years at CQU & UESTC,” Photon. Sens. 2(2), 97–117 (2012). [CrossRef]  

8. 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,” OFS 2010. Proc. SPIE 7503(75031O), 75031O (2009). [CrossRef]  

9. H. F. Martins, S. Martín-López, P. Corredera, M. L. Filograno, O. Frazão, and M. Gonzalez-Herráez, “Phase-sensitive optical time domain reflectometer assisted by first-order raman amplification for distributed vibration sensing over> 100 km,” J. Lightwave Technol. 8(32), 1510–1518 (2014). [CrossRef]  

10. Y. Lu, T. Zhu, L. Chen, and X. Bao, “Distributed vibration sensor based on coherent detection of phase-OTDR,” J. Lightwave Technol. 27, 3243–3249 (2010).

11. Z. Qin, L. Chen, and X. Bao, “Wavelet denoising method for improving detection performance of distributed vibration sensor,” IEEE Photon. Technol. Lett. 24(7), 542–544 (2012). [CrossRef]  

12. G. P. Agrawal, Applications of Nonlinear Fiber Optics, 2nd ed. (Academic Press, 2008).

13. I. Daubechies, Ten lecture on wavelets, CBMS series, Philadelphia: SIMA,1992.

References

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  1. H. F. Taylor and C. E. Lee, “Apparatus and method for fiber optic intrusion sensing,” U. S. Patent 5, 194 847, March 16, 1993.
  2. H. F. Martins, S. Martin-Lopez, P. Corredera, P. Salgado, O. Frazão, and M. González-Herráez, “Modulation instability-induced fading in phase-sensitive optical time-domain reflectometry,” Opt. Lett. 38(6), 872–874 (2013).
    [Crossref] [PubMed]
  3. J. Park, W. Lee, and H. F. Taylor, “A fiber optic intrusion sensor with the configuration of an optical time domain reflectometer using coherent interference of Rayleigh backscattering,” Proc. SPIE 3555, 49–56 (1998).
    [Crossref]
  4. K. N. Choi and H. F. Taylor, “Spectrally stable Er-fiber laser for application in phase-sensitive optical time-domain reflectrometry,” IEEE Photon. Technol. Lett. 15(3), 386–388 (2003).
    [Crossref]
  5. J. C. Juarez, E. W. Maier, K. N. Choi, and H. F. Taylor, “Distributed fiber-optic intrusion sensor system,” J. Lightwave Technol. 23(6), 2081–2087 (2005).
    [Crossref]
  6. H. F. Martins, S. Martin-Lopez, P. Corredera, M. L. Filograno, O. Frazao, and M. Gonzalez-Herraez, “Coherent noise reduction in high visibility phase-sensitive optical time domain reflectometer for distributed sensing of ultrasonic waves,” J. Lightwave Technol. 31(23), 3631–3637 (2013).
    [Crossref]
  7. Y. J. Rao, “OFS research over the last 10 years at CQU & UESTC,” Photon. Sens. 2(2), 97–117 (2012).
    [Crossref]
  8. 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,” OFS 2010. Proc. SPIE 7503(75031O), 75031O (2009).
    [Crossref]
  9. H. F. Martins, S. Martín-López, P. Corredera, M. L. Filograno, O. Frazão, and M. Gonzalez-Herráez, “Phase-sensitive optical time domain reflectometer assisted by first-order raman amplification for distributed vibration sensing over> 100 km,” J. Lightwave Technol. 8(32), 1510–1518 (2014).
    [Crossref]
  10. Y. Lu, T. Zhu, L. Chen, and X. Bao, “Distributed vibration sensor based on coherent detection of phase-OTDR,” J. Lightwave Technol. 27, 3243–3249 (2010).
  11. Z. Qin, L. Chen, and X. Bao, “Wavelet denoising method for improving detection performance of distributed vibration sensor,” IEEE Photon. Technol. Lett. 24(7), 542–544 (2012).
    [Crossref]
  12. G. P. Agrawal, Applications of Nonlinear Fiber Optics, 2nd ed. (Academic Press, 2008).
  13. I. Daubechies, Ten lecture on wavelets, CBMS series, Philadelphia: SIMA,1992.

2014 (1)

H. F. Martins, S. Martín-López, P. Corredera, M. L. Filograno, O. Frazão, and M. Gonzalez-Herráez, “Phase-sensitive optical time domain reflectometer assisted by first-order raman amplification for distributed vibration sensing over> 100 km,” J. Lightwave Technol. 8(32), 1510–1518 (2014).
[Crossref]

2013 (2)

2012 (2)

Y. J. Rao, “OFS research over the last 10 years at CQU & UESTC,” Photon. Sens. 2(2), 97–117 (2012).
[Crossref]

Z. Qin, L. Chen, and X. Bao, “Wavelet denoising method for improving detection performance of distributed vibration sensor,” IEEE Photon. Technol. Lett. 24(7), 542–544 (2012).
[Crossref]

2010 (1)

Y. Lu, T. Zhu, L. Chen, and X. Bao, “Distributed vibration sensor based on coherent detection of phase-OTDR,” J. Lightwave Technol. 27, 3243–3249 (2010).

2009 (1)

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,” OFS 2010. Proc. SPIE 7503(75031O), 75031O (2009).
[Crossref]

2005 (1)

2003 (1)

K. N. Choi and H. F. Taylor, “Spectrally stable Er-fiber laser for application in phase-sensitive optical time-domain reflectrometry,” IEEE Photon. Technol. Lett. 15(3), 386–388 (2003).
[Crossref]

1998 (1)

J. Park, W. Lee, and H. F. Taylor, “A fiber optic intrusion sensor with the configuration of an optical time domain reflectometer using coherent interference of Rayleigh backscattering,” Proc. SPIE 3555, 49–56 (1998).
[Crossref]

Bao, X.

Z. Qin, L. Chen, and X. Bao, “Wavelet denoising method for improving detection performance of distributed vibration sensor,” IEEE Photon. Technol. Lett. 24(7), 542–544 (2012).
[Crossref]

Y. Lu, T. Zhu, L. Chen, and X. Bao, “Distributed vibration sensor based on coherent detection of phase-OTDR,” J. Lightwave Technol. 27, 3243–3249 (2010).

Chen, L.

Z. Qin, L. Chen, and X. Bao, “Wavelet denoising method for improving detection performance of distributed vibration sensor,” IEEE Photon. Technol. Lett. 24(7), 542–544 (2012).
[Crossref]

Y. Lu, T. Zhu, L. Chen, and X. Bao, “Distributed vibration sensor based on coherent detection of phase-OTDR,” J. Lightwave Technol. 27, 3243–3249 (2010).

Choi, K. N.

J. C. Juarez, E. W. Maier, K. N. Choi, and H. F. Taylor, “Distributed fiber-optic intrusion sensor system,” J. Lightwave Technol. 23(6), 2081–2087 (2005).
[Crossref]

K. N. Choi and H. F. Taylor, “Spectrally stable Er-fiber laser for application in phase-sensitive optical time-domain reflectrometry,” IEEE Photon. Technol. Lett. 15(3), 386–388 (2003).
[Crossref]

Corredera, P.

Filograno, M. L.

H. F. Martins, S. Martín-López, P. Corredera, M. L. Filograno, O. Frazão, and M. Gonzalez-Herráez, “Phase-sensitive optical time domain reflectometer assisted by first-order raman amplification for distributed vibration sensing over> 100 km,” J. Lightwave Technol. 8(32), 1510–1518 (2014).
[Crossref]

H. F. Martins, S. Martin-Lopez, P. Corredera, M. L. Filograno, O. Frazao, and M. Gonzalez-Herraez, “Coherent noise reduction in high visibility phase-sensitive optical time domain reflectometer for distributed sensing of ultrasonic waves,” J. Lightwave Technol. 31(23), 3631–3637 (2013).
[Crossref]

Frazao, O.

Frazão, O.

H. F. Martins, S. Martín-López, P. Corredera, M. L. Filograno, O. Frazão, and M. Gonzalez-Herráez, “Phase-sensitive optical time domain reflectometer assisted by first-order raman amplification for distributed vibration sensing over> 100 km,” J. Lightwave Technol. 8(32), 1510–1518 (2014).
[Crossref]

H. F. Martins, S. Martin-Lopez, P. Corredera, P. Salgado, O. Frazão, and M. González-Herráez, “Modulation instability-induced fading in phase-sensitive optical time-domain reflectometry,” Opt. Lett. 38(6), 872–874 (2013).
[Crossref] [PubMed]

Gonzalez-Herraez, M.

Gonzalez-Herráez, M.

H. F. Martins, S. Martín-López, P. Corredera, M. L. Filograno, O. Frazão, and M. Gonzalez-Herráez, “Phase-sensitive optical time domain reflectometer assisted by first-order raman amplification for distributed vibration sensing over> 100 km,” J. Lightwave Technol. 8(32), 1510–1518 (2014).
[Crossref]

González-Herráez, M.

Juarez, J. C.

Lee, W.

J. Park, W. Lee, and H. F. Taylor, “A fiber optic intrusion sensor with the configuration of an optical time domain reflectometer using coherent interference of Rayleigh backscattering,” Proc. SPIE 3555, 49–56 (1998).
[Crossref]

Lu, Y.

Y. Lu, T. Zhu, L. Chen, and X. Bao, “Distributed vibration sensor based on coherent detection of phase-OTDR,” J. Lightwave Technol. 27, 3243–3249 (2010).

Luo, J.

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,” OFS 2010. Proc. SPIE 7503(75031O), 75031O (2009).
[Crossref]

Luo, X. D.

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,” OFS 2010. Proc. SPIE 7503(75031O), 75031O (2009).
[Crossref]

Maier, E. W.

Martin-Lopez, S.

Martín-López, S.

H. F. Martins, S. Martín-López, P. Corredera, M. L. Filograno, O. Frazão, and M. Gonzalez-Herráez, “Phase-sensitive optical time domain reflectometer assisted by first-order raman amplification for distributed vibration sensing over> 100 km,” J. Lightwave Technol. 8(32), 1510–1518 (2014).
[Crossref]

Martins, H. F.

Park, J.

J. Park, W. Lee, and H. F. Taylor, “A fiber optic intrusion sensor with the configuration of an optical time domain reflectometer using coherent interference of Rayleigh backscattering,” Proc. SPIE 3555, 49–56 (1998).
[Crossref]

Qin, Z.

Z. Qin, L. Chen, and X. Bao, “Wavelet denoising method for improving detection performance of distributed vibration sensor,” IEEE Photon. Technol. Lett. 24(7), 542–544 (2012).
[Crossref]

Ran, Z. L.

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,” OFS 2010. Proc. SPIE 7503(75031O), 75031O (2009).
[Crossref]

Rao, Y. J.

Y. J. Rao, “OFS research over the last 10 years at CQU & UESTC,” Photon. Sens. 2(2), 97–117 (2012).
[Crossref]

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,” OFS 2010. Proc. SPIE 7503(75031O), 75031O (2009).
[Crossref]

Salgado, P.

Taylor, H. F.

J. C. Juarez, E. W. Maier, K. N. Choi, and H. F. Taylor, “Distributed fiber-optic intrusion sensor system,” J. Lightwave Technol. 23(6), 2081–2087 (2005).
[Crossref]

K. N. Choi and H. F. Taylor, “Spectrally stable Er-fiber laser for application in phase-sensitive optical time-domain reflectrometry,” IEEE Photon. Technol. Lett. 15(3), 386–388 (2003).
[Crossref]

J. Park, W. Lee, and H. F. Taylor, “A fiber optic intrusion sensor with the configuration of an optical time domain reflectometer using coherent interference of Rayleigh backscattering,” Proc. SPIE 3555, 49–56 (1998).
[Crossref]

Yue, J. F.

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,” OFS 2010. Proc. SPIE 7503(75031O), 75031O (2009).
[Crossref]

Zhou, Z.

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,” OFS 2010. Proc. SPIE 7503(75031O), 75031O (2009).
[Crossref]

Zhu, T.

Y. Lu, T. Zhu, L. Chen, and X. Bao, “Distributed vibration sensor based on coherent detection of phase-OTDR,” J. Lightwave Technol. 27, 3243–3249 (2010).

IEEE Photon. Technol. Lett. (2)

K. N. Choi and H. F. Taylor, “Spectrally stable Er-fiber laser for application in phase-sensitive optical time-domain reflectrometry,” IEEE Photon. Technol. Lett. 15(3), 386–388 (2003).
[Crossref]

Z. Qin, L. Chen, and X. Bao, “Wavelet denoising method for improving detection performance of distributed vibration sensor,” IEEE Photon. Technol. Lett. 24(7), 542–544 (2012).
[Crossref]

J. Lightwave Technol. (4)

H. F. Martins, S. Martín-López, P. Corredera, M. L. Filograno, O. Frazão, and M. Gonzalez-Herráez, “Phase-sensitive optical time domain reflectometer assisted by first-order raman amplification for distributed vibration sensing over> 100 km,” J. Lightwave Technol. 8(32), 1510–1518 (2014).
[Crossref]

Y. Lu, T. Zhu, L. Chen, and X. Bao, “Distributed vibration sensor based on coherent detection of phase-OTDR,” J. Lightwave Technol. 27, 3243–3249 (2010).

J. C. Juarez, E. W. Maier, K. N. Choi, and H. F. Taylor, “Distributed fiber-optic intrusion sensor system,” J. Lightwave Technol. 23(6), 2081–2087 (2005).
[Crossref]

H. F. Martins, S. Martin-Lopez, P. Corredera, M. L. Filograno, O. Frazao, and M. Gonzalez-Herraez, “Coherent noise reduction in high visibility phase-sensitive optical time domain reflectometer for distributed sensing of ultrasonic waves,” J. Lightwave Technol. 31(23), 3631–3637 (2013).
[Crossref]

OFS 2010. Proc. SPIE (1)

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,” OFS 2010. Proc. SPIE 7503(75031O), 75031O (2009).
[Crossref]

Opt. Lett. (1)

Photon. Sens. (1)

Y. J. Rao, “OFS research over the last 10 years at CQU & UESTC,” Photon. Sens. 2(2), 97–117 (2012).
[Crossref]

Proc. SPIE (1)

J. Park, W. Lee, and H. F. Taylor, “A fiber optic intrusion sensor with the configuration of an optical time domain reflectometer using coherent interference of Rayleigh backscattering,” Proc. SPIE 3555, 49–56 (1998).
[Crossref]

Other (3)

H. F. Taylor and C. E. Lee, “Apparatus and method for fiber optic intrusion sensing,” U. S. Patent 5, 194 847, March 16, 1993.

G. P. Agrawal, Applications of Nonlinear Fiber Optics, 2nd ed. (Academic Press, 2008).

I. Daubechies, Ten lecture on wavelets, CBMS series, Philadelphia: SIMA,1992.

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Figures (6)

Fig. 1
Fig. 1 Experimental setup of Φ-OTDR system with 1-st BRA and heterodyne detection.
Fig. 2
Fig. 2 (a) The optical spectrum (observed at the output of BPF2) and (b) RS curve when PR = 0 and Pp = −19.4dBm.
Fig. 3
Fig. 3 RS curves in different power combinations of probe pulses and Raman pump. The red lines are the simulated RS curves.
Fig. 4
Fig. 4 Auto-spectrum of 97.51km when the driven signal with different frequencies are applied.
Fig. 5
Fig. 5 (a) Auto-power spectrum of vibration along the fiber when the vibration frequency at 97.51km is 375Hz. (b) Amplitude at 375Hz of each position. The sub graph in (b) is the enlarged part around 97.51km.
Fig. 6
Fig. 6 (a) Steel pipeline with optical fiber cable attached. (b) Original time series (blue line) and slowly varying noises (red line) when chiseling the pipe. (c) Extracted disturbance series when chiseling on the pipe. The red * represent the peak of the impulses generated by chiseling the pipe.

Equations (2)

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d P P dz = g R P R P P α P P P
ξ d P R dz = ω R ω S g R P R P P α R P R

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