Identifications and classifications of human locomotion using Rayleigh-enhanced distributed fiber acoustic sensors with deep neural networks

Peng, Zhaoqiang; Wen, Hao; Jian, Jianan; Gribok, Andrei V.; Wang, Mohan; Huang, Sheng; Liu, Hu; Mao, Zhi-Hong; Chen, Kevin P.

doi:10.1038/s41598-020-77147-2

Cited by 30 publications

(10 citation statements)

References 32 publications

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“…9(b), considerable improvement is evident in detected vibration SNR while lowering the noise floor compared to standard SMF. The acoustic SNR was increased by 29,18,17,16,20,19,11 and 11 dB at the frequency of 100, 200, 500, 1000, 1500, 2000, 2500 and 3000 Hz, respectively. It is evident that the enhanced fiber cable exhibits an improved vibration sensitivity by increasing Rayleigh backscatter while adding little attenuation thereby lowering the noise floor of the sensor to improve the acoustic SNR of the sensing system.…”

Section: Experimental Setup and Lab-scale Demonstration Of Pipeline M...mentioning

confidence: 99%

Pilot-Scale Testing of Natural Gas Pipeline Monitoring Based on Phase-OTDR and Enhanced Scatter Optical Fiber Cable

Lalam,

Westbrook,

Naeem

et al. 2023

Preprint

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In this paper, we present the results of lab and pilot-scale testing of a continuously enhanced backscattering, or Rayleigh enhanced fiber cable that can improve distributed acoustic sensing performance. In addition, the Rayleigh-enhanced fiber is embedded within a tight buffered cable configuration to withstand and be compatible for field applications. The sensing fiber cable exhibits a Rayleigh enhancement of 13 dB compared to standard silica single-mode fiber while maintaining low attenuation of ≤0.4 dB/km. We built a phase-sensitive optical time domain reflectometry system to interrogate the enhanced backscattering fiber cable both in lab and pilot-scale tests. In the laboratory experiment, we analyzed the vibration performance of the enhanced backscattering fiber cable and compared it with the standard single-mode telecom fiber. Afterward, we field validated for natural gas pipeline vibration monitoring using a 4-inch diameter steel pipeline operating at a fixed pressure level of 1000 psi, and a flow rate of 5, 10, 15, and 20 ft/s. The feasibility of gas pipeline monitoring with the proposed enhanced backscattering fiber cable shows a substantial increase in vibration sensing performance. The pilot-scale testing results demonstrated in this paper enable pipeline operators to perform accurate flow monitoring, leak detection, third-party intrusion detection, and continuous pipeline ground movement.

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Section: Experimental Setup and Lab-scale Demonstration Of Pipeline M...mentioning

confidence: 99%

Pilot-Scale Testing of Natural Gas Pipeline Monitoring Based on Phase-OTDR and Enhanced Scatter Optical Fiber Cable

Lalam,

Westbrook,

Naeem

et al. 2023

Preprint

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show abstract

“…In addition to highway monitoring, the possibilities of more detailed tracking that includes the movement of people using fiber sensors are also being explored. As an example, a sensor with directed scattering centers recorded the movement of one and two people walking and running in different shoes in work by Z. Peng et al [ 104 ]. Machine learning met both human identification and locomotion recognition requirements, with an accuracy of over 76.25% when using supervised and 77.65% when using unsupervised machine learning algorithms.…”

Section: Das In the Engineering Sciences (Andrey A Zhirnov And Konsta...mentioning

confidence: 99%

Scientific Applications of Distributed Acoustic Sensing: State-of-the-Art Review and Perspective

Gorshkov

Yüksel

Fotiadi

et al. 2022

Sensors

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This work presents a detailed review of the development of distributed acoustic sensors (DAS) and their newest scientific applications. It covers most areas of human activities, such as the engineering, material, and humanitarian sciences, geophysics, culture, biology, and applied mechanics. It also provides the theoretical basis for most well-known DAS techniques and unveils the features that characterize each particular group of applications. After providing a summary of research achievements, the paper develops an initial perspective of the future work and determines the most promising DAS technologies that should be improved.

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“…Many research works that combine DAS + PRS suffer from issues related to pattern classification design and experimental evaluation setups: real classification and results are not presented [45][46][47][48][49][50]; lack of details on both the system description and experimental conditions [25,[51][52][53][54][55][56][57][58][59]; data are not obtained in realistic field environments [15,25,49,[51][52][53]58,[60][61][62][63][64][65][66][67][68][69][70][71][72][73][74][75][76][77]; the lack of testing signals/classes to recognize [15,49,54,63,65,[69][70]…”

Section: Motivation and Organization Of This Papermentioning

confidence: 99%

A Multi-Position Approach in a Smart Fiber-Optic Surveillance System for Pipeline Integrity Threat Detection

et al. 2021

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We present a new pipeline integrity surveillance system for long gas pipeline threat detection and classification. The system is based on distributed acoustic sensing with phase-sensitive optical time domain reflectometry (ϕ-OTDR) and pattern recognition for event classification. The proposal incorporates a multi-position approach in a Gaussian Mixture Model (GMM)-based pattern classification system which operates in a real-field scenario with a thorough experimental procedure. The objective is exploiting the availability of vibration-related data at positions nearby the one actually producing the main disturbance to improve the robustness of the trained models. The system integrates two classification tasks: (1) machine + activity identification, which identifies the machine that is working over the pipeline along with the activity being carried out, and (2) threat detection, which aims to detect suspicious threats for the pipeline integrity (independently of the activity being carried out). For the machine + activity identification mode, the multi-position approach for model training obtains better performance than the previously presented single-position approach for activities that show consistent behavior and high energy (between 6% and 11% absolute) with an overall increase of 3% absolute in the classification accuracy. For the threat detection mode, the proposed approach gets an 8% absolute reduction in the false alarm rate with an overall increase of 4.5% absolute in the classification accuracy.

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Identifications and classifications of human locomotion using Rayleigh-enhanced distributed fiber acoustic sensors with deep neural networks

Cited by 30 publications

References 32 publications

Pilot-Scale Testing of Natural Gas Pipeline Monitoring Based on Phase-OTDR and Enhanced Scatter Optical Fiber Cable

Pilot-Scale Testing of Natural Gas Pipeline Monitoring Based on Phase-OTDR and Enhanced Scatter Optical Fiber Cable

Scientific Applications of Distributed Acoustic Sensing: State-of-the-Art Review and Perspective

A Multi-Position Approach in a Smart Fiber-Optic Surveillance System for Pipeline Integrity Threat Detection

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