Improved Perturbation Detection in Direct Detected -OTDR Systems using Matched Filtering

Abstract

Nuisance Alarm Rate (NAR) is critical in φ-OTDR perturbation detection systems. We present in this letter a novel matched filtering-based feature extractor which aims to noise reduction so that the detection system gets improved performance. This feature extractor requires a small number of data vectors to be acquired which is combined with a random forestbased machine learning strategy to significantly reduce the NAR. In addition, since the number of data vectors is small, this system can also be useful for time-sensitive detection applications.

Variational Mode Decomposition-Based Threat Classification for Fiber Optic Distributed Acoustic Sensing

“…Therefore, by substituting the solutions given in (13) and (15) into the ADMM method, an algorithm for VMD can be achieved. It can be summarized as provided in the following procedure [22]:…”

“…Hence, it provides an efficient way for the monitoring of multi-point acoustic vibrations along the cable. Its effectiveness has been demonstrated in various applications such as crack detection of structures [4,5], railroad monitoring [6,7], traffic flow detection [8], vehicle detection [9], and intrusion detection [10][11][12][13][14][15][16][17][18].…”

“…It has already known that the backscattered signal sensed in a phase-OTDR based DAS system has generally quite low signal-to-noise ratio (SNR) which highly affects the vibration detection capability of the systems. Thus, several methods such as heterodyning [4], Fourier transforming [5], multidimension comprehensive analysis [7], polarization diversity detection [10], two-dimensional edge detection [11], Raman amplification [12], signal-noise separation [13], adaptive temporal/match filtering [14,15], Wavelet denoising [6,8,9,16], multi-scale permutation entropy and the zero-crossing rate [17], and difference in time-frequency domain [18] have been used to improve the threat/event detection performance. Although these methods provide promising results, it is still necessary to open new corridors in order to improve the quality of weak Rayleigh backscattered signal in event detection.…”

Phase Noise Characterization in Phase-Sensitive OTDR Systems

“…P HASE-OTDR has gained more attention among the scientific community in the last decade. It is due to a very large scope of its use in many applications including intrusion recognition systems [1]- [3], pipeline leakage management [4], warning systems [5], [6], damage tolerance detection [7], railway line management [8], [9] and structural health monitoring [10]. These applications are preferred due to distributed nature of the phase-sensitive OTDR systems and extending the range of fiber under test (FUT) is a key research target of the distributed optical fiber sensing community.…”

An Improved Rotation-Based Privacy Preserving Classification in Web Mining Using Naïve Bayes Classifier

“…Perturbed data is classified by various machine learning approaches and it is compared with the original data to evaluate the performance of the proposed system (Landgrebe & Duin, 2008;Du et al, 2018). In Internet of Things, the large numbers of data streams are traversed across the web and there is a huge demand to ensure the user's privacy (Adeel et al, 2019;Kiran & Vasumathi, 2019). The data privacy preservation and sharing is achieved in IoT with the help of data perturbation and cryptography processes (Chen et al, 2007;Tanuwidjaja et al, 2019).…”