The security pre-warning system of underground pipelines was traditionally designed by electronic sensors, usually suffering from intrinsic flawssuch as too scattered monitoring points and poor anti-interference performance. To overcome these disadvantages, a distributed optical fiber temperature and strain sensing system based on Brillouin Optical Time Domain Reflectometer (BOTDR) is designed and developed for underground pipelines security monitoring. In this paper, the sensing mechanism of temperature and strain sensing is analyzed and a BOTDR experimental scheme is presented. Meanwhile, the kernel software program is developed for signal demodulation. Then, the integrated BOTDR instrument is designed compactly and evaluated by temperature and strain measurement experiments, for respectively simulating pipeline leakage and deformation. The experimental results show that the sensing range of 10.268 km is achieved with a spatial resolution of 1.15 m. The nonlinear error is less than 1% FSS over the temperature and strain change of 30~90°C and 0-15000με.
In this paper, the composite interferometric distributed optical fiber vibration sensing technology based on a two-path unbalanced Mach-Zehnder/Sagnac linear interferometric structure is proposed. Firstly, the laser interference mechanism and vibration positioning principle of this system are theoretically analyzed, and the vibration positioning algorithm with the time-delay estimation based on the improved generalized cross-correlation principle is proposed. Secondly, the experimental system is built and double photodetectors are used to obtain the two-path interferometric signal with a certain time delay, and the high-precision time delay signal is obtained with the help of conjugate multiplication and digital filtering algorithm. The experimental results show that the system can accurately locate different types of vibration signals with a 65 km sensing fiber, and the location limitation of broadband vibration signals for a single-channel interferometric structure can be resolved. This system is expected to be popularized and applied in fields such as leakage monitoring of coalbed methane pipelines.
Brillouin optical time domain reflectometer (BOTDR) has attracted extensive attention due to its advantages of one-end access and long-distance measurement. The measurement accuracy and sensing range of BOTDR are affected by the system signal-to-noise ratio (SNR), which is closely related to the characteristics of the probe light pulse. In this paper, the influence of two characteristics of probe light on SNR is theoretically analyzed and experimentally verified, including the extinction ratio (ER) and peak power. Firstly, the theoretical model of probe pulse extinction ratio (ER) and SNR in the BOTDR is established, and the SNR distribution versus different ER is analyzed. Both numerical simulation and experimental verification show that the SNR was enhanced with the increase of ER. Besides, the SNRs under different pulse peak power are also evaluated. The experimental results show that the SNR increases along with the peak power at the beginning but decreases when the peak power exceed a certain value. The research results provide a reference for selecting the appropriate probe pulse features in BOTDR for higher SNR.
A novel pattern recognition method based on relevant vector machine for optical fiber vibration sensor is proposed to meet the requirement of accurate identification of long-distance pipeline leakage. The sensing system is based on Sagnac interferometer, which is suitable for vibration signal detection. The initial vibration signals are firstly pretreated by the wavelet de-noising method. Then, the wavelet decomposition algorithm is utilized to obtain decomposition coefficients at all levels to build feature vectors. Furthermore, the relevant vector machine is presented as a classifier to identify three types of vibration signals, including pipeline leakage, human tapping and human walking. Experimental results demonstrate that the proposed method can discriminate three threat events with an average recognition rate above 85% with a 4-km-long sensing fiber, which can satisfy actual application requirements.
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