Acoustic inspection system with unmanned aerial vehicles for offshore wind turbines: A real case study

Wind energy has become fundamental in the global transition towards renewable energies, with the deployment of larger and more complex wind turbines. CMS play a crucial role in early fault detection, enhancing productivity while decreasing downtimes and maintenance costs to ensure the optimal perfor...

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Detalles Bibliográficos
Autores: Segovia Ramírez, Isaac, García Márquez, Fausto Pedro, Bernalte Sánchez, Pedro José, Peinado Gonzalo, Alfredo
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universidad Autónoma de Madrid
Repositorio:Biblos-e Archivo. Repositorio Institucional de la UAM
Idioma:inglés
OAI Identifier:oai:dnet:biblosearchi::a9053ad7754e32b663d224bcc156fc5f
Acceso en línea:https://hdl.handle.net/10486/773380
https://dx.doi.org/10.1016/j.measurement.2025.117226
Access Level:acceso abierto
Palabra clave:Offshore wind Turbines
Acoustic Analysis
Maintenance Management
Unmanned Aerial Vehicle
Structural Heal Monitoring
Telecomunicaciones
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spelling Acoustic inspection system with unmanned aerial vehicles for offshore wind turbines: A real case studySegovia Ramírez, IsaacGarcía Márquez, Fausto PedroBernalte Sánchez, Pedro JoséPeinado Gonzalo, AlfredoOffshore wind TurbinesAcoustic AnalysisMaintenance ManagementUnmanned Aerial VehicleStructural Heal MonitoringTelecomunicacionesWind energy has become fundamental in the global transition towards renewable energies, with the deployment of larger and more complex wind turbines. CMS play a crucial role in early fault detection, enhancing productivity while decreasing downtimes and maintenance costs to ensure the optimal performance and viability of the wind energy industry. This paper presents a novel non-destructive testing system embedded in an unmanned aerial vehicle designed to acquire acoustic data from rotating wind turbine components. This approach develops pre-processing and filtering methodologies based on wavelet transform, Fast Fourier or energy transformation to avoid undesired noise sources, e.g., the rotor of the drones or the environment, and to obtain patterns associated with the real state of the wind turbine. The implementation of acoustic monitoring in wind turbines is a novelty in the current state of the art, and this methodology is tested in an operating offshore wind turbine. The experiments incorporate an external condition monitoring system and introduce noise records from simulated mechanical faults. The results demonstrate that all the noise sources and faulty and healthy scenarios can be differentiated, proving the reliability of the methodology and the robustness of the fault detection approachThe work reported herein was supported financially by the Ministerio de Ciencia e Innovación (Spain) and the European Regional Development Fund, under the Research Grant WindSound project (Reference: PID2021-125278OB-I00)ElservierEscuela Politécnica SuperiorDepartamento de Tecnología Electrónica y de las ComunicacionesHardware and Control Technology LaboratoryGobierno de España20252025-03-07research articlehttp://purl.org/coar/resource_type/c_2df8fbb1VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10486/773380https://dx.doi.org/10.1016/j.measurement.2025.117226reponame:Biblos-e Archivo. Repositorio Institucional de la UAMinstname:Universidad Autónoma de MadridInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:dnet:biblosearchi::a9053ad7754e32b663d224bcc156fc5f2026-06-23T12:46:27Z
dc.title.none.fl_str_mv Acoustic inspection system with unmanned aerial vehicles for offshore wind turbines: A real case study
title Acoustic inspection system with unmanned aerial vehicles for offshore wind turbines: A real case study
spellingShingle Acoustic inspection system with unmanned aerial vehicles for offshore wind turbines: A real case study
Segovia Ramírez, Isaac
Offshore wind Turbines
Acoustic Analysis
Maintenance Management
Unmanned Aerial Vehicle
Structural Heal Monitoring
Telecomunicaciones
title_short Acoustic inspection system with unmanned aerial vehicles for offshore wind turbines: A real case study
title_full Acoustic inspection system with unmanned aerial vehicles for offshore wind turbines: A real case study
title_fullStr Acoustic inspection system with unmanned aerial vehicles for offshore wind turbines: A real case study
title_full_unstemmed Acoustic inspection system with unmanned aerial vehicles for offshore wind turbines: A real case study
title_sort Acoustic inspection system with unmanned aerial vehicles for offshore wind turbines: A real case study
dc.creator.none.fl_str_mv Segovia Ramírez, Isaac
García Márquez, Fausto Pedro
Bernalte Sánchez, Pedro José
Peinado Gonzalo, Alfredo
author Segovia Ramírez, Isaac
author_facet Segovia Ramírez, Isaac
García Márquez, Fausto Pedro
Bernalte Sánchez, Pedro José
Peinado Gonzalo, Alfredo
author_role author
author2 García Márquez, Fausto Pedro
Bernalte Sánchez, Pedro José
Peinado Gonzalo, Alfredo
author2_role author
author
author
dc.contributor.none.fl_str_mv Escuela Politécnica Superior
Departamento de Tecnología Electrónica y de las Comunicaciones
Hardware and Control Technology Laboratory
Gobierno de España
dc.subject.none.fl_str_mv Offshore wind Turbines
Acoustic Analysis
Maintenance Management
Unmanned Aerial Vehicle
Structural Heal Monitoring
Telecomunicaciones
topic Offshore wind Turbines
Acoustic Analysis
Maintenance Management
Unmanned Aerial Vehicle
Structural Heal Monitoring
Telecomunicaciones
description Wind energy has become fundamental in the global transition towards renewable energies, with the deployment of larger and more complex wind turbines. CMS play a crucial role in early fault detection, enhancing productivity while decreasing downtimes and maintenance costs to ensure the optimal performance and viability of the wind energy industry. This paper presents a novel non-destructive testing system embedded in an unmanned aerial vehicle designed to acquire acoustic data from rotating wind turbine components. This approach develops pre-processing and filtering methodologies based on wavelet transform, Fast Fourier or energy transformation to avoid undesired noise sources, e.g., the rotor of the drones or the environment, and to obtain patterns associated with the real state of the wind turbine. The implementation of acoustic monitoring in wind turbines is a novelty in the current state of the art, and this methodology is tested in an operating offshore wind turbine. The experiments incorporate an external condition monitoring system and introduce noise records from simulated mechanical faults. The results demonstrate that all the noise sources and faulty and healthy scenarios can be differentiated, proving the reliability of the methodology and the robustness of the fault detection approach
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-03-07
dc.type.none.fl_str_mv research article
http://purl.org/coar/resource_type/c_2df8fbb1
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10486/773380
https://dx.doi.org/10.1016/j.measurement.2025.117226
url https://hdl.handle.net/10486/773380
https://dx.doi.org/10.1016/j.measurement.2025.117226
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/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-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elservier
publisher.none.fl_str_mv Elservier
dc.source.none.fl_str_mv reponame:Biblos-e Archivo. Repositorio Institucional de la UAM
instname:Universidad Autónoma de Madrid
instname_str Universidad Autónoma de Madrid
reponame_str Biblos-e Archivo. Repositorio Institucional de la UAM
collection Biblos-e Archivo. Repositorio Institucional de la UAM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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