OptaSense&amp;#x00AE; Distributed Acoustic and Seismic Sensing Performance for Multi-threat, Multi-environment Border Monitoring

Duckworth, Gregory L.; Owen, Archibald Alexander; Worsley, Jerry; Stephenson, Henry

doi:10.1109/eisic.2013.70

Cited by 8 publications

(3 citation statements)

References 3 publications

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“…Duckworth et al investigated DAS responses to different intrusion events and found that DAS can not only capture the vibration signals of personnel footsteps but also respond well to intrusion events that are difficult to detect using conventional security technologies, such as digging, gunshots, underground excavation, and aircraft intrusion [ 96 ]. This fully demonstrates the application potential of DAS in border intrusion monitoring.…”

Section: Applications Of Das In Linear Infrastructure Monitoringmentioning

confidence: 99%

Distributed Acoustic Sensing for Monitoring Linear Infrastructures: Current Status and Trends

Zhu

Liu

Wang

et al. 2022

Sensors

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Linear infrastructures, such as railways, tunnels, and pipelines, play essential roles in economic and social development worldwide. However, under the influence of geohazards, earthquakes, and human activities, linear infrastructures face the potential risk of damage and may not function properly. Current monitoring systems for linear infrastructures are mainly based on non-contact detection (InSAR, UAV, GNSS, etc.) and geotechnical instrumentation (extensometers, inclinometers, tiltmeters, piezometers, etc.) techniques. Regarding monitoring sensitivity, frequency, and coverage, most of these methods have some shortcomings, which make it difficult to perform the accurate, real-time, and comprehensive monitoring of linear infrastructures. Distributed acoustic sensing (DAS) is an emerging sensing technology that has rapidly developed in recent years. Due to its unique advantages in long-distance, high-density, and real-time monitoring, DAS arrays have shown broad application prospects in many fields, such as oil and gas exploration, seismic observation, and subsurface imaging. In the field of linear infrastructure monitoring, DAS has gradually attracted the attention of researchers and practitioners. In this paper, recent research and the development activities of applying DAS to monitor different types of linear infrastructures are critically reviewed. The sensing principles are briefly introduced, as well as the main features. This is followed by a summary of recent case studies and some critical problems associated with the implementation of DAS monitoring systems in the field. Finally, the challenges and future trends of this research area are presented.

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Section: Applications Of Das In Linear Infrastructure Monitoringmentioning

confidence: 99%

Distributed Acoustic Sensing for Monitoring Linear Infrastructures: Current Status and Trends

Zhu

Liu

Wang

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…In addition to the signal acquisition system, signal to noise ratio (SNR) values of the collected signals should be taken into consideration. In this context, there are several studies in which the SNR values have been examined in the literature ( [5] and [9]). However, the signals have either a high SNR value or have been increased to higher SNR levels by using various signal processing methods in these studies.…”

Section: Snr Bağımlı Veri üRetimi Kullanılarak Fiber Optik Dağıtılmış Akustikmentioning

confidence: 99%

Deep Learning Based Threat Classification for Fiber Optic Distributed Acoustic Sensing Using SNR Dependent Data Generation

Uzundurukan¹,

Kara²

2020

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“…Although the sensing properties from a C-OTDR technique have some downsides compared to OFDR or φ-OTDR (decreased spatial resolution and gauge length), they also have substantial benefits such as a wide range and easy applicability and thus have been used for many different applications, including linear asset protection, border monitoring, train traffic management and detecting natural hazards. Duckworth et al and Owen et al [60][61][62] set up a scalable system architecture that enables border monitoring, a high security perimeter and linear asset protection. Timofeev et al [63,64] developed a rail traffic management system utilizing C-OTDR.…”

mentioning

confidence: 99%

Optical Fibres for Condition Monitoring of Railway Infrastructure—Encouraging Data Source or Errant Effort?

Vidović

Marschnig

2020

Applied Sciences

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The condition of railway infrastructure is currently assessed by track recording cars, wayside equipment, onboard monitoring techniques and visual inspections. These data sources deliver valuable information for infrastructure managers on the asset’s condition but are mostly carried out in time-based intervals. This paper examines the potential of fibre optic cables, which are already installed in cable troughs alongside railway tracks, to monitor railway infrastructure conditions. The sensing technique, known as distributed acoustic/vibration sensing (DAS/DVS), relies on the effect of Rayleigh scattering and transforms the optical fibre into an array of “virtual microphones” in the thousands. This sensing method has the ability to be used over long distances and thus provide information about the events taking place in the proximity of the monitored asset in real-time. This study outlines the potential of DAS for the identification of different track conditions and isolated track defects. The results are linked to asset data of the infrastructure manager to identify the root cause of the detected signal anomalies and pattern. A methodology such as this allows for condition-based and component-specific maintenance planning and execution and avoids the installation of additional sensors. DAS can pave the way toward a permanent and holistic assessment of railway tracks.

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OptaSense® Distributed Acoustic and Seismic Sensing Performance for Multi-threat, Multi-environment Border Monitoring

Cited by 8 publications

References 3 publications

Distributed Acoustic Sensing for Monitoring Linear Infrastructures: Current Status and Trends

Distributed Acoustic Sensing for Monitoring Linear Infrastructures: Current Status and Trends

Deep Learning Based Threat Classification for Fiber Optic Distributed Acoustic Sensing Using SNR Dependent Data Generation

Optical Fibres for Condition Monitoring of Railway Infrastructure—Encouraging Data Source or Errant Effort?

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