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Highly discriminative and adaptive feature extraction method based on NMF–MFCC for event recognition of Φ-OTDR

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Abstract

To enhance the capability of phase-sensitive optical time domain reflectometers ($\Phi$-OTDR) to recognize disturbance events, an improved adaptive feature extraction method based on NMF–MFCC is proposed, which replaces the fixed filter bank used in the traditional method to extract the mel-frequency cepstral coefficient (MFCC) features by a spectral structure obtained from the $\Phi$-OTDR signal spectrum using nonnegative matrix factorization (NMF). Three typical events on fences are set as recognition targets in our experiments, and the results show that the NMF–MFCC features have higher distinguishability, with the corresponding recognition accuracy reaching 98.47%, which is 7% higher than that using the traditional MFCC features.

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Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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