Discussion on the sensitivity of optical cables based on distributed acoustic sensing

Shang, Ying; Wang, Chen; Ni, Jiasheng; Zhao, Wei; Li, Chang; Cao, Bing; Huang, Shaoyong; Wang, Chang; Peng, Gang-Ding

doi:10.1007/s10043-019-00547-x

Cited by 7 publications

(3 citation statements)

References 23 publications

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“…In the context of all-dielectric underground optic cable searchings, DAS can be used to locate and detect the presence of underground cables. When an acoustic disturbance, such as digging or drilling, occurs near a buried cable, the disturbance causes small vibrations in the ground, which in turn cause vibrations in the cable [4][5][6]. These cable vibrations can be detected and located by a DAS system, allowing for the precise identification of the cable's location and path.…”

Section: Introductionmentioning

confidence: 99%

All-dielectric fiber-optic cable route search method

Gureev,

Dashkov,

Shaban

2023

Optical Technologies for Telecommunications 2022

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The article discusses the use of Distributed Acoustic Sensing technology in locating underground all-dielectric optic cables. DAS uses fiber optic cables to detect acoustic vibrations along the cable's length caused by digging or drilling, allowing for precise identification of the cable's location and path without excavation or other intrusive search methods. DAS provides high-resolution data over long distances, making it more accurate than traditional search methods like geo-radar or GPS markers. The article proposes a localization algorithm for detecting the path of all-dielectric optical cables using DAS technology, based on a combination of approximate and point estimates of cable location. The algorithm is tested on a testing ground of a section of an optical communication line, demonstrating the ability to determine the area of optical cable laying with a radius of up to 5 meters in real-time.

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Section: Introductionmentioning

confidence: 99%

All-dielectric fiber-optic cable route search method

Gureev,

Dashkov,

Shaban

2023

Optical Technologies for Telecommunications 2022

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“…Distributed optical fiber acoustic sensing has gained wide attention in recent years owing to its prominent advantages in terms of its high sensitivity, electrical passivity, and strong resistance to corrosion and electromagnetic interference [1][2][3]. In recent years, distributed acoustic sensors have received considerable research attention and exhibited a good application foreground in the areas of 3D vertical seismic profiling [4], traffic flow detection [5], partial discharge monitoring [6], pipeline integrity protecting [7], hydraulic fracturing monitoring [8], vehicle detection and classification [9], drone detection and localization [10], and so on.…”

Section: Introductionmentioning

confidence: 99%

Signal-to-Noise Ratio Improvement for Phase-Sensitive Optical Time-Domain Reflectometry Using a Genetic Least Mean Square Method

Liu,

Zhou

et al. 2023

Photonics

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In this paper, a genetic least mean square (GLMS) method is proposed to improve the signal-to-noise ratio (SNR) of acoustic signal reconstruction in a phase-sensitive optical time-domain reflectometry system. The raw demodulated signal is processed via applying the least mean square criterion. The SNR of the processed signal was calculated and served as the objective function in the fitness evaluation procedure. The genetic operations of the population selection, crossover, and mutation are sequentially performed and repeated until the suspensive condition is reached. Through multiple iterations, the GLMS method continuously optimized the population to find the optimal solution. Experimental results demonstrate that the SNR is substantially improved by 14.37–23.60 dB in the monotonic scale audio signal test from 60 to 1000 Hz. Furthermore, the improvement of the phase reconstruction of a human voice audio signal is also validated by exploiting the proposed GLMS method.

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“…How to select or design the most suitable optical cable for a specific application scenario is currently a hot research topic. The common approach is to connect diverse kinds of optical cables to a DAS system and place them in their respective application scenarios, gauge the disparities in their response to the target signal, and pick the optimal optical cable from among them [21][22][23]. However, this method can only discover comparatively superior choices from current communication optical cables and is not a purpose-built, custom sensing cable.…”

Section: Introductionmentioning

confidence: 99%

How the Material Characteristics of Optical Fibers and Soil Influence the Measurement Results of Distributed Acoustic Sensing

Jiang,

Liang,

Tong

et al. 2023

Sensors

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Fiber optic distributed acoustic sensing (DAS) technology is widely used in security surveillance and geophysical survey applications. The response of the DAS system to external vibrations varies with different types of fiber optic cable connections. The mechanism of mutual influence between the cable’s characteristics and DAS measurement results remains unclear. This study proposed a dynamic model of the interaction between the optical cable and the soil, analyzed the impact of the dynamic parameters of the optical cable and soil on the sensitivity of the DAS system, and validated the theoretical analysis through experiments. The findings suggest that augmenting the cable’s bending stiffness 5.5-fold and increasing its unit mass 4.2-fold result in a discernible reduction of the system’s response to roughly 0.15 times of its initial magnitude. Cables with lower unit mass and bending stiffness are more sensitive to vibration signals. This research provides a foundation for optimizing vibration-enhanced fiber optic cables and broadening the potential usage scenarios for DAS systems.

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Discussion on the sensitivity of optical cables based on distributed acoustic sensing

Cited by 7 publications

References 23 publications

All-dielectric fiber-optic cable route search method

All-dielectric fiber-optic cable route search method

Signal-to-Noise Ratio Improvement for Phase-Sensitive Optical Time-Domain Reflectometry Using a Genetic Least Mean Square Method

How the Material Characteristics of Optical Fibers and Soil Influence the Measurement Results of Distributed Acoustic Sensing

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