This paper presents a multi-class support vector machine (MCSVM) based high-efficiency events discrimination method for asymmetric dual Mach-Zehnder interferometers (ADMZI) distributed infrared fiber vibration sensor. This method combined empirical mode decomposition (EMD), kurtosis characteristics with MCSVM, which can improve the recognition rate effectively. Filed experimental results demonstrate that the proposed method can discriminate four common invasive events (climbing the fence, knocking the cable, cutting the fence, and waggling the fence) with an average recognition rate above 90.9%, which can satisfy actual application requirements.
We proposed a gain compensation method to overcome the amplitude fading induced by the gain-bandwidth product (GBP) of the detector, which will seriously deteriorate the positioning accuracy of the distributed disturbance sensor at a long sensing range. To guarantee the performance of this method, we used the time-frequency distribution of the interference signal to distinguish the normal signal and the one need to compensate. A positioning measurement experiment using an asymmetric dual Mach-Zehnder interferometer (ADMZI) was carried out to verify the effectiveness of the proposed method. The experiment result showed that the sensing range can reach 121km, which was improved by over 40% compared to the traditional positioning method without gain compensation.
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