A multi-position approach in a smart fiber-optic surveillance system for pipeline integrity threat detection

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 (?-OTDR) and pattern recognition for event classification. The proposal incorp...

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Detalles Bibliográficos
Autores: Tejedor Noguerales, Javier, Macías Guarasa, Javier|||0000-0002-3303-3963, Fidalgo Martins, Hugo|||0000-0003-3927-8125, Martín López, Sonia|||0000-0001-5203-6206, González Herráez, Miguel|||0000-0003-2555-2971
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universidad de Alcalá (UAH)
Repositorio:e_Buah Biblioteca Digital Universidad de Alcalá
Idioma:inglés
OAI Identifier:oai:ebuah.uah.es:10017/64547
Acceso en línea:http://hdl.handle.net/10017/64547
https://dx.doi.org/10.3390/electronics10060712
Access Level:acceso abierto
Palabra clave:Pipeline integrity threat monitoring
Distributed acoustic sensing
Fiber-optic
ϕ-OTDR
Pattern recognition
Electrónica
Electronics
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spelling A multi-position approach in a smart fiber-optic surveillance system for pipeline integrity threat detectionTejedor Noguerales, JavierMacías Guarasa, Javier|||0000-0002-3303-3963Fidalgo Martins, Hugo|||0000-0003-3927-8125Martín López, Sonia|||0000-0001-5203-6206González Herráez, Miguel|||0000-0003-2555-2971Pipeline integrity threat monitoringDistributed acoustic sensingFiber-opticϕ-OTDRPattern recognitionElectrónicaElectronicsWe 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 (?-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.Ministerio de Economía y CompetitividadAgencia Estatal de InvestigaciónUniversidad de AlcaláMinisterio de Ciencia e InnovaciónMDPI20212021-03-18journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10017/64547https://dx.doi.org/10.3390/electronics10060712reponame:e_Buah Biblioteca Digital Universidad de Alcaláinstname:Universidad de Alcalá (UAH)InglésengMinisterio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 Not available TIN2016-75982-C2-1-R DETECCION SEMANTICA MULTISENSORIAL DE SITUACIONES ANOMALAS EN ENTORNOS SIN RESTRICCIONESAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 TIN2016-80939-R RECONSTRUCCION DE OBJETOS DEFORMABLES A PARTIR DE IMAGENES Y SUS APLICACIONES A LA REALIDAD AUMENTADA EN CIRUGIA MINIMAMENTE INVASIVAUAH Not available CCG2019%2FIA-024UAH Not available CCG2020%2FIA-043Ministerio de Ciencia e Innovación http://dx.doi.org/10.13039/501100004837 Not available IJCI-2017-33856Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 RTI2018-097957-B-C33 TECNICAS AVANZADAS DE GENERACION, AMPLIFICACION Y MEDIDA DE SEÑALES OPTICAS COMPLEJAS EN FIBRA OPTICAAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 RTI2018-095324-B-I00 GESTION ADAPTATIVA Y PROACTIVA DE LA ENFERMEDAD CRONICA MEDIANTE UNA PLATAFORMA VESTIBLEopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:ebuah.uah.es:10017/645472026-06-18T11:13:07Z
dc.title.none.fl_str_mv A multi-position approach in a smart fiber-optic surveillance system for pipeline integrity threat detection
title A multi-position approach in a smart fiber-optic surveillance system for pipeline integrity threat detection
spellingShingle A multi-position approach in a smart fiber-optic surveillance system for pipeline integrity threat detection
Tejedor Noguerales, Javier
Pipeline integrity threat monitoring
Distributed acoustic sensing
Fiber-optic
ϕ-OTDR
Pattern recognition
Electrónica
Electronics
title_short A multi-position approach in a smart fiber-optic surveillance system for pipeline integrity threat detection
title_full A multi-position approach in a smart fiber-optic surveillance system for pipeline integrity threat detection
title_fullStr A multi-position approach in a smart fiber-optic surveillance system for pipeline integrity threat detection
title_full_unstemmed A multi-position approach in a smart fiber-optic surveillance system for pipeline integrity threat detection
title_sort A multi-position approach in a smart fiber-optic surveillance system for pipeline integrity threat detection
dc.creator.none.fl_str_mv Tejedor Noguerales, Javier
Macías Guarasa, Javier|||0000-0002-3303-3963
Fidalgo Martins, Hugo|||0000-0003-3927-8125
Martín López, Sonia|||0000-0001-5203-6206
González Herráez, Miguel|||0000-0003-2555-2971
author Tejedor Noguerales, Javier
author_facet Tejedor Noguerales, Javier
Macías Guarasa, Javier|||0000-0002-3303-3963
Fidalgo Martins, Hugo|||0000-0003-3927-8125
Martín López, Sonia|||0000-0001-5203-6206
González Herráez, Miguel|||0000-0003-2555-2971
author_role author
author2 Macías Guarasa, Javier|||0000-0002-3303-3963
Fidalgo Martins, Hugo|||0000-0003-3927-8125
Martín López, Sonia|||0000-0001-5203-6206
González Herráez, Miguel|||0000-0003-2555-2971
author2_role author
author
author
author
dc.subject.none.fl_str_mv Pipeline integrity threat monitoring
Distributed acoustic sensing
Fiber-optic
ϕ-OTDR
Pattern recognition
Electrónica
Electronics
topic Pipeline integrity threat monitoring
Distributed acoustic sensing
Fiber-optic
ϕ-OTDR
Pattern recognition
Electrónica
Electronics
description 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 (?-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.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-03-18
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10017/64547
https://dx.doi.org/10.3390/electronics10060712
url http://hdl.handle.net/10017/64547
https://dx.doi.org/10.3390/electronics10060712
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 Not available TIN2016-75982-C2-1-R DETECCION SEMANTICA MULTISENSORIAL DE SITUACIONES ANOMALAS EN ENTORNOS SIN RESTRICCIONES
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 TIN2016-80939-R RECONSTRUCCION DE OBJETOS DEFORMABLES A PARTIR DE IMAGENES Y SUS APLICACIONES A LA REALIDAD AUMENTADA EN CIRUGIA MINIMAMENTE INVASIVA
UAH Not available CCG2019%2FIA-024
UAH Not available CCG2020%2FIA-043
Ministerio de Ciencia e Innovación http://dx.doi.org/10.13039/501100004837 Not available IJCI-2017-33856
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 RTI2018-097957-B-C33 TECNICAS AVANZADAS DE GENERACION, AMPLIFICACION Y MEDIDA DE SEÑALES OPTICAS COMPLEJAS EN FIBRA OPTICA
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 RTI2018-095324-B-I00 GESTION ADAPTATIVA Y PROACTIVA DE LA ENFERMEDAD CRONICA MEDIANTE UNA PLATAFORMA VESTIBLE
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:e_Buah Biblioteca Digital Universidad de Alcalá
instname:Universidad de Alcalá (UAH)
instname_str Universidad de Alcalá (UAH)
reponame_str e_Buah Biblioteca Digital Universidad de Alcalá
collection e_Buah Biblioteca Digital Universidad de Alcalá
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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