Abstract

Null frequencies in the spectrum of a phase difference signal are used for intrusion localization since their values are associated with the position of intrusion in a Sagnac interferometer. However, searching the null frequencies individually is troublesome and unreliable for localization. In this paper, an algorithm which directly captures the interval of null frequencies is proposed to achieve a simpler and more robust intrusion localization. By applying the modified spectrum to a second fast Fourier transform, the interval responds as multiple peaks in the resulting location curve. After determining the values of the base peak and its harmonic peaks, the intrusion’s distance can be localized. Intrusions are applied at a position of 130 km in a sensing fiber. Due to the resolution increase as peak order, localization performance of 2nd harmonic peak is 25 m, which is 34% better than the base peaks. By calculating the average of the localization results by all remarkable peaks, localization performance improves by 47% in laboratory experiments and by 24% in practical applications over the previous single-peak localization algorithm.

© 2016 Optical Society of America

Improved location algorithm for multiple intrusions in distributed Sagnac fiber sensing system

He Wang, Qizhen Sun, Xiaolei Li, Jianghai Wo, Perry Ping Shum, and Deming Liu
Opt. Express 22(7) 7587-7597 (2014)

High-spatial-resolution localization algorithm based on cascade deconvolution in a distributed Sagnac interferometer invasion monitoring system

Shaohua Pi, Bingjie Wang, Jiang Zhao, and Qi Sun
Appl. Opt. 55(29) 8180-8184 (2016)

Multievent localization for loop-based Sagnac sensing system using machine learning

Jameel Ali, Ahmed Almaiman, Amr M. Ragheb, Maged A. Esmail, Esam M. Almohimmah, and Saleh A. Alshebeili
Opt. Express 31(15) 24005-24024 (2023)

Surface recovery algorithm in white light interferometry based on combined white light phase shifting and fast Fourier transform algorithms

Quangsang Vo, Fengzhou Fang, Xiaodong Zhang, and Huimin Gao
Appl. Opt. 56(29) 8174-8185 (2017)

Underwater gas pipeline leakage source localization by distributed fiber-optic sensing based on particle swarm optimization tuning of the support vector machine

Yue Huang, Qiang Wang, Lilian Shi, and Qihua Yang
Appl. Opt. 55(2) 242-247 (2016)