Significant research efforts have focused on techniques for alleviating the nuisance alarm
rate (NAR) in the field of ϕ-OTDR pattern recognition systems. Unfortunately, ephemeral …

Event classification with machine learning methods, has now become the research spotlight
for phase sensitive optical time domain reflectometer (Ф-OTDR, also referred to as DAS or …

The phase sensitive optical time-domain reflectometer (φ-OTDR), or in some applications
called distributed acoustic sensing (DAS), has been a popularly used technology for long …

Distributed acoustic sensors (DAS) are effective apparatuses that are widely used in many
application areas for recording signals of various events with very high spatial resolution …

We propose a hybrid model named channel attention based temporal convolutional network
combined with spatial attention and bidirectional long short-term memory network (ATCN-SA …

The phase-sensitive time-domain reflectometer (φ-OTDR) has been popularly used for
events detection over a long period of time. In this study, the events classification methods …

To address the problem of decreased recognition accuracy of event samples in practical
phase-sensitive optical time-domain reflectometer (Φ-OTDR) monitoring scenarios due to …

An end-to-end deep learning model based on the deep belief network (DBN) and gated
recurrent unit (GRU) is proposed to recognize the single disturbance events and composite …

To enhance the capability of phase-sensitive optical time domain reflectometers (Φ-OTDR)
to recognize disturbance events, an improved adaptive feature extraction method based on …

Nuisance Alarm Rate (NAR) is critical in-OTDR perturbation detection systems. We present
in this letter a novel matched filtering-based feature extractor which aims to noise reduction …