The demand for distributed acoustic sensors, which are capable of reconstructing the amplitude, frequency, and phase of an acoustic field, is increasing. These sensors are typically realized by phase-sensitive optical time-domain reflectometry (Φ-OTDR). However, common Φ-OTDR systems suffer from a fading phenomenon, which causes amplitude fluctuation on Rayleigh backscattering traces, and the scattered light may not have enough intensity in some regions. These areas have low amplitude backscattering that may be even lower than the system noise floor during some periods of time. Therefore, we cannot reconstruct the phase signal properly in such low intensity areas. Systems with multiple frequencies have been proposed to achieve fading suppression. However, online data processing of such schemes remains a challenge, especially for continuous in-field applications. Prediction of fading must be performed in real time. Any delay caused by massive calculations is not acceptable. In this paper, a continuous fading suppression method based on a Φ-OTDR system with three different probe frequencies is presented as well as a tracking algorithm for selecting the optimum probe signal for any time, which predicts the occurrence of fading before it actually occurs. The performance of the proposed method has been experimentally evaluated and statistically analyzed. The distortion induced by the fading effect could Manuscript
The last years have witnessed the wide application of Distributed Acoustic Sensor (DAS) systems in several fields, such as submarine cable monitoring, seismic wave detection, structural health monitoring, etc. Due to their distributed measurement ability and high sensitivity, DAS systems can be employed as a promising tool for the phase sensitive optical time domain reflectometry (Φ-OTDR). However, it is also well-known that the traditional Φ-OTDR system suffers from Rayleigh backscattering (RBS) fading effects, which induce dead zones in the measurement results. Worse still, in practice it is difficult to achieve the optimum matching between spatial resolution (SR) and signal to noise ratio (SNR). Further, the overall frequency response range (FRR) of the traditional Φ-OTDR is commonly limited by the length of the fiber in order to prevent RBS signals from overlapping with each other. Additionally, it is usually difficult to reconstruct high frequency vibration signals accurately for long range monitoring. Aiming at solving these problems, we introduce frequency division multiplexing (FDM) that makes it easier to improve the system performance with less system structure changes. We propose several novel Φ-OTDR schemes based on Frequency Division Multiplexing (FDM) technology to solve the above problems. Experimental results showed that the distortion induced by fading effects could be suppressed to 1.26%; when the SR of Φ-OTDR is consistent with the length of the vibration region, the SNR of the sensing system is improved by 3 dB compared to the average SNR with different SRs; vibration frequencies up to 440 kHz have been detected along 330 m artificial microstructures. Thus, the proposed sensing system offers a promising solution for the performance enhancement of DAS systems that could achieve high SNR, broadband FRR and dead zone-free measurements at the same time.
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