Sensitivity of Distributed Acoustic Sensor Based on Sagnac Interferometer

Choban, T.V.; Zhirnov, A. A.; Stepanov, K. V.; Khan, Roman I.; Koshelev, Kirill I.; Pnev, Alexey B.; Karasik, Valeriy E.

doi:10.1109/iclo54117.2022.9839896

Cited by 3 publications

(3 citation statements)

References 3 publications

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“…Specifically, in this equation provided, n is the number of cycles of the signal that should be included in the excitation (based upon the Hanning window (period)). The assumed excitation amplitude is 0.003 inches, based on calibration between piezo actuator voltage and simulation excitation displacement from past work [8], [9]. This signal was defined in ANSYS to simulate the effects of an actuator, which is a representative excitation waveform when compared with existing commercial ultrasonic acoustic NDE technologies [24], [26] The corresponding wave in the frequency domain.…”

Section: The Excitation Concept Of Guided Ultrasonic Waves (Ugws)mentioning

confidence: 99%

“…The quasi-distributed/point fiber vibration/acoustic sensor technologies include fiber Bragg grating (FBG) [6], Fabry-Pérot [7], and Multimodal interference [8]. Various interferometric configurations include; the Sagnac interferometer [9], the Mach-Zehnder interferometer (MZI) [10], and polarization-OTDR (POTDR) [11]. Fiber optic sensors are known for being resilient in harsh environments and capable of distributed interrogation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Real-Time Pipe Structure Change Detection and Classification using Distributed Acoustic Fiber Sensors Based on Convolutional Neural Network (CNN) Models

Zhang¹,

Venketeswaran²,

Wright³

et al. 2023

Preprint

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This study proposes a machine-learning-based framework for detecting mechanical damage in pipelines, utilizing physics-informed datasets collected from simulations for mechanical damage. The framework provides an effective workflow from dataset generation to damage detection and identification for three types of pipeline events: welds, clamps, and corrosion defects. While the study initially focused on optimizing the CNN structure using various advanced optimizers, it also investigated the impact of sensing systems on data classification and the effect of noise on classification performance. The study's analysis highlights the importance of selecting the appropriate sensing system for the specific application. The authors also found that the proposed framework is robust to experimentally relevant levels of noise, suggesting its applicability in real-world scenarios where noise is present. Overall, this study contributes to the development of a more reliable and effective method for detecting mechanical damage in pipelines. The proposed framework provides an effective workflow for damage detection and identification, and the findings on the impact of sensing systems and noise on classification performance add to its robustness and reliability.

show abstract

Section: The Excitation Concept Of Guided Ultrasonic Waves (Ugws)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Real-Time Pipe Structure Change Detection and Classification using Distributed Acoustic Fiber Sensors Based on Convolutional Neural Network (CNN) Models

Zhang¹,

Venketeswaran²,

Wright³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The quasi-distributed/point fiber vibration/acoustic sensor technologies include fiber Bragg grating (FBG) [ 8 ], Fabry–Pérot [ 9 ], and multimodal interference [ 10 ]. Various interferometric configurations include the Sagnac interferometer [ 11 ], the Mach–Zehnder interferometer (MZI) [ 12 ], and polarization-OTDR (POTDR) [ 13 ]. Fiber optic sensors are known for being resilient in harsh environments and capable of distributed interrogation.…”

Section: Introductionmentioning

confidence: 99%

Quasi-Distributed Fiber Sensor-Based Approach for Pipeline Health Monitoring: Generating and Analyzing Physics-Based Simulation Datasets for Classification

Zhang

Venketeswaran

Wright

et al. 2023

Sensors

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This study presents a framework for detecting mechanical damage in pipelines, focusing on generating simulated data and sampling to emulate distributed acoustic sensing (DAS) system responses. The workflow transforms simulated ultrasonic guided wave (UGW) responses into DAS or quasi-DAS system responses to create a physically robust dataset for pipeline event classification, including welds, clips, and corrosion defects. This investigation examines the effects of sensing systems and noise on classification performance, emphasizing the importance of selecting the appropriate sensing system for a specific application. The framework shows the robustness of different sensor number deployments to experimentally relevant noise levels, demonstrating its applicability in real-world scenarios where noise is present. Overall, this study contributes to the development of a more reliable and effective method for detecting mechanical damage to pipelines by emphasizing the generation and utilization of simulated DAS system responses for pipeline classification efforts. The results on the effects of sensing systems and noise on classification performance further enhance the robustness and reliability of the framework.

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Fiber Optic Temperature Sensor Based on the Harmonic Vernier Effect Generated by Two Sagnac Interferometers

Yang,

Zhang,

et al. 2024

IEEE Sensors J.

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Sensitivity of Distributed Acoustic Sensor Based on Sagnac Interferometer

Cited by 3 publications

References 3 publications

Real-Time Pipe Structure Change Detection and Classification using Distributed Acoustic Fiber Sensors Based on Convolutional Neural Network (CNN) Models

Real-Time Pipe Structure Change Detection and Classification using Distributed Acoustic Fiber Sensors Based on Convolutional Neural Network (CNN) Models

Quasi-Distributed Fiber Sensor-Based Approach for Pipeline Health Monitoring: Generating and Analyzing Physics-Based Simulation Datasets for Classification

Fiber Optic Temperature Sensor Based on the Harmonic Vernier Effect Generated by Two Sagnac Interferometers

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