A simple and effective interference fading suppression method for Φ-OTDR using optimal peak-seeking is proposed. This method can reconstruct the vibration signal with high fidelity under the premise of using only ordinary single-mode sensing fiber without changing the structure of the traditional Φ-OTDR system. Based on the data after interference suppression, we applied different machine learning models to recognize the invasive events category. The promising results show potential applications of Φ-OTDR equipment and future implementation with machine learning algorithms.
The phase-sensitive optical time-domain reflectometry (Φ-OTDR) has been developed rapidly as a fully fiber-optic distributed vibration sensing technology. However, the demodulation technique based on the phase term would induce a serious false alarm problem due to the signal fading effect. An effective method to suppress fading-induced false alarms in the Φ-OTDR system is proposed, which is based on the suppression mask and numerical relationship between phase and amplitudes of Rayleigh backscattering. The performance of the proposed method has been experimentally demonstrated in both laboratory environment and in-field situation test. Without any hardware addition in a traditional Φ-OTDR equipment, false alarms rate can be reduced from 4.81% to 0.15%, whereas low missing alarms rate can be achieved at the same time. In-field results show that this work provides a low-cost solution to enhance the performance for real-life engineering application of the phase-discrimination Φ-OTDR system.
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