119941 20240319081019.0 doi 10.3390/s22176515 sideral 130505 ART-2022-130505 eng Almudévar, Antonio Universidad de Zaragoza Unsupervised anomaly detection applied to F-OTDR 2022 Access copy available to the general public Unrestricted 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. info:eu-repo/grantAgreement/ES/DGA/T20-20R info:eu-repo/grantAgreement/ES/DGA/T36-20R info:eu-repo/grantAgreement/ES/MICINN-AEI/RTC2019-007207-4/AEI/10.13039/501100011033 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 3.9 2022 CHEMISTRY, ANALYTICAL 26 / 86 = 0.302 2022 Q2 T1 INSTRUMENTS & INSTRUMENTATION 19 / 63 = 0.302 2022 Q2 T1 ENGINEERING, ELECTRICAL & ELECTRONIC 100 / 274 = 0.365 2022 Q2 T2 0.764 2022 Instrumentation 2022 Q1 Analytical Chemistry 2022 Q1 Medicine (miscellaneous) 2022 Q2 Information Systems 2022 Q2 Biochemistry 2022 Q2 Atomic and Molecular Physics, and Optics 2022 Q2 Electrical and Electronic Engineering 2022 Q2 6.8 2022 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Sevillano, Pascual Universidad de Zaragoza (orcid)0000-0002-4094-3826 Vicente, Luis Universidad de Zaragoza (orcid)0000-0003-4391-5203 Preciado-Garbayo, Javier (orcid)0000-0001-5898-8777 Ortega, Alfonso Universidad de Zaragoza (orcid)0000-0002-3886-7748 2002 385 Universidad de Zaragoza Dpto. Física Aplicada Área Física Aplicada 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 22, 17 (2022), 6515 [14 pp] Sensors Sensors 1424-8220 2123291 http://zaguan.unizar.es/record/119941/files/texto_completo.pdf Versión publicada 2667888 http://zaguan.unizar.es/record/119941/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:119941 articulos driver 2024-03-18-15:57:37 ARTICLE