Unsupervised anomaly detection applied to F-OTDR

Almudévar, Antonio (Universidad de Zaragoza) ; Sevillano, Pascual (Universidad de Zaragoza) ; Vicente, Luis (Universidad de Zaragoza) ; Preciado-Garbayo, Javier ; Ortega, Alfonso (Universidad de Zaragoza)

Resumen: Distributed acoustic sensors (DASs) based on direct-detection Φ-OTDR use the light–matter interaction between light pulses and optical fiber to detect mechanical events in the fiber environment. The signals received in Φ-OTDR come from the coherent interference of the portion of the fiber illuminated by the light pulse. Its high sensitivity to minute phase changes in the fiber results in a severe reduction in the signal to noise ratio in the intensity trace that demands processing techniques be able to isolate events. For this purpose, this paper proposes a method based on Unsupervised Anomaly Detection techniques which make use of concepts from the field of deep learning and allow the removal of much of the noise from the Φ-OTDR signals. The fact that this method is unsupervised means that no human-labeled data are needed for training and only event-free data are used for this purpose. Moreover, this method has been implemented and its performance has been tested with real data showing promising results.

Idioma: Inglés

DOI: 10.3390/s22176515

Año: 2022

Publicado en: Sensors 22, 17 (2022), 6515 [14 pp]
ISSN: 1424-8220

Factor impacto JCR: 3.9 (2022)

Categ. JCR: CHEMISTRY, ANALYTICAL rank: 26 / 86 = 0.302 (2022) - Q2 - T1
Categ. JCR: INSTRUMENTS & INSTRUMENTATION rank: 19 / 63 = 0.302 (2022) - Q2 - T1
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 100 / 274 = 0.365 (2022) - Q2 - T2

Factor impacto CITESCORE: 6.8 - Engineering (Q1) - Chemistry (Q1) - Biochemistry, Genetics and Molecular Biology (Q2) - Physics and Astronomy (Q1)

Factor impacto SCIMAGO: 0.764 - Instrumentation (Q1) - Analytical Chemistry (Q1) - Medicine (miscellaneous) (Q2) - Information Systems (Q2) - Biochemistry (Q2) - Atomic and Molecular Physics, and Optics (Q2) - Electrical and Electronic Engineering (Q2)

Financiación: info:eu-repo/grantAgreement/ES/DGA/T20-20R
Financiación: info:eu-repo/grantAgreement/ES/DGA/T36-20R
Financiación: info:eu-repo/grantAgreement/ES/MICINN-AEI/RTC2019-007207-4/AEI/10.13039/501100011033

Tipo y forma: Article (Published version)

Área (Departamento): Área Física Aplicada (Dpto. Física Aplicada)
Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)