Abstract
In this paper, aiming at the problem of vibration event classification based on phase sensitive optical time-domain reflectometer (Φ-OTDR), we propose an efficient multi class event recognition scheme based on Variational Mode Decomposition (VMD). The signals collected by optical fiber sensors are preprocessed by the VMD algorithm, and then the features of the signals are extracted by Mel Frequency Cepstral Coefficients (MFCC). Finally, the extracted features are classified and identified by using machine learning algorithm. In order to improve the reliability of identification, the VMD algorithm can be used to decompose the signal into different modes. We extract and identify the features of each mode signal. Finally, the result with the highest number of occurrences is taken as the identification result. Six different vehicle vibration signals are classified and identified, and the recognition accuracy is 97.7%.
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