Raman distributed fiber optic sensors are mainly based on the Raman scattering effect in optical fibers as well as optical time-domain reflection techniques to achieve fully distributed sensing along the optical fiber distribution. The spatial resolution, as an important index of this system, reflects the minimum fiber length that the sensing system can resolve when measuring the temperature field. The spatial resolution of the existing kilometer-scale Raman distributed fiber optic sensing scheme is limited to the meter scale, and the application of distributed fiber optic sensors on some special occasions is severely restricted. In order to solve this problem, the team of Chenyi Wang and Jian Li from Taiyuan University of Technology proposed a high spatial resolution Raman distributed fiber optic sensing technique based on the chaotic correlation method.

Chaotic quadratic correlation algorithm

      In the article, a new chaotic Raman distributed fiber optic sensing scheme is proposed by using chaotic laser as a new type of sensing light source, the Raman backward scattering characteristics of continuous and pulsed chaotic laser in the sensing fiber and the modulation principle of FUT on the chaotic Raman scattering signals are investigated, the basic mathematical model is provided for the experiments of the chaotic ROTDR system, and the theoretical basis for the breakthrough of the limitations of spatial resolution by the pulse width of differential reconstruction and one-time correlation algorithm of the chaotic Raman backward scattering signals is analyzed specifically.
      In order to solve the problem that the experimental results are greatly affected by noise, a quadratic correlation algorithm is proposed in the paper, according to the analysis of the characteristics of the Raman scattering signal, each point in the Raman backward scattering signal acquired by the system is a superposition of the backward scattering signals corresponding to half a pulse width. This process weakens the random undulation property of chaos and makes the autocorrelation property of chaos unavailable. Therefore, a differential reconstruction process is needed to extract the chaotic random fluctuation characteristics and temperature information of each point. At the same time, this algorithm can reduce the influence of the fiber attenuation coefficient on the experimental results.

Fig. 1. The orange part demonstrates the principle associated with the chaotic quadratic correlation algorithm. The blue shaded part demonstrates that the chaotic pulse signal is correlated with the differential reconstruction signal, and the useful information containing temperature information is amplified by using the chaotic autocorrelation property to form the correlation peaks on the time series, and the location information of the measured area along the sensing fiber is obtained. The chaotic time-domain compression demodulation mechanism between the temperature change information and the chaotic correlation peaks is further demonstrated, and the propagation equations for the differential reconstruction and quadratic correlation of chaotic Raman backscattered signals are established.

High spatial resolution ROTDR platform construction

      Based on the principle of chaotic ROTDR system temperature measurement, the team set up a chaotic ROTDR experimental platform. The effects of chaotic pulse width, spectral shape, chaotic bandwidth, number of chaotic sub-pulses, amplitude probability distribution, incoming power and system delay on the sensing distance and spatial resolution of the chaotic ROTDR system are investigated from theoretical and experimental perspectives. The experiments are carried out to ensure that the above influencing factors are in the optimal state, and the results obtained can accurately locate the position of the temperature change signals. Finally, a spatial resolution of 10 cm is achieved at a sensing distance of 1.5 km.

Fig. 2. A conventional laser with a center wavelength of 1550 nm passes through a circulator and is modulated into continuous chaotic light by a single feedback structure consisting of an attenuator, polarization controller, and fiber coupler. The continuous chaotic laser light is modulated into a chaotic pulsed laser light by an optical pulse modulator (SOA), which is then passed through an erbium-doped fiber amplifier (EDFA) to achieve chaotic pulsed laser amplification. The chaotic pulse is then split into two parts by a 1:99 optocoupler, 1% of which is used as the pulse reference signal for the algorithm, and 99% of which enters the sensing fiber through a Wavelength Division Multiplexer (WDM) to generate Raman backscattered signals. Stokes light. The anti-Stokes and pulse signals are converted into electrical signals by an avalanche photodiode (APD) and captured by an oscilloscope (OSC), respectively.

      The chaotic ROTDR system was experimentally demonstrated to be able to break the suppression of spatial resolution by pulse width, finally achieving spatial resolution on the order of centimeters using a 50 ns pulse width. Within the limitations of the existing spatial resolution theory, the spatial resolution of this scheme is improved by a factor of 50 over the conventional scheme.
      The Raman distributed fiber optic sensing technique based on the chaotic correlation method optimizes the spatial resolution performance of the traditional sensors, extends the application scenarios of the Raman distributed fiber optic sensors, and has great application potential in some occasions requiring high spatial resolution, providing a new research direction for optical chaos and fiber optic sensing.

（Supported by National Natural Science Foundation of China (NSFC) under Grants (62075151, 62205234, 62105234); National Key Research and Development Program of China (2022YFA1404201); Supported by Fundamental Research Program of Shanxi Province (202103021223042); Supported by Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi. Supported by Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering.）

References:

1.Jian Li, Xinxin Zhou, Yang Xu, et al., Slope-assisted Raman distributed optical fiber sensing, Photonics Research, 10(1), 205-213 (2022).
2.Jian Li, Chenyi Wang, Kangyi Cao, et al., Breakthrough the physical barrier on spatial resolution in Raman distributed fiber sensing using chaotic correlation demodulation, APL Photonics, 8, 076105 (2023). 
3.Jian Li, Baoqiang Yan, Mingjiang Zhang*, et al., Long-range Raman distributed fiber temperature sensor with early warning model for fire detection and prevention, IEEE Sensors Journal, 19(10): 3711-3717 (2019). 
4.Jian Li, Qian Zhang, Tao Yu, et al., R-DTS with heat transfer functional model for perceiving the surrounding temperature, IEEE Sensors Journal, 20(2): 816-822 (2020). 
5.Xinxin Zhou, Jian Li, Yang Xu, et al., Chaos Raman optical time-domain reflectometry for millimeter-level spatial resolution temperature sensing, Journal of Lightwave Technology, 39(23), 7529-7538 (2021). 
6.Jian Li, Yunting Li, MingjiangZhang, et al., Performance improvement of Raman distributed temperature system by using noise suppression, Photonic Sensors, 8(2): 103-113 (2018). 
7.Jian Li, Xinxin Zhou, Zitong Yin, et al., Reconstruction compression correlation demodulation for Raman OTDR, Advanced Photonics Research, 2:2100047 (2021).