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dc.contributor.authorHoxha, Ervin
dc.contributor.authorVidal Seguí, Yolanda
dc.contributor.authorPozo Montero, Francesc
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Matemàtica Aplicada
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtiques
dc.date.accessioned2020-11-20T13:44:12Z
dc.date.available2020-11-20T13:44:12Z
dc.date.issued2020-10-05
dc.identifier.citationHoxha, E.; Vidal, Y.; Pozo, F. Damage diagnosis for offshore wind turbine foundations based on the fractal dimension. "Applied sciences", 5 Octubre 2020, vol. 10, núm. 19, p. 6972:1-6972:24.
dc.identifier.issn1454-5101
dc.identifier.urihttp://hdl.handle.net/2117/332722
dc.description.abstractCost-competitiveness of offshore wind depends heavily in its capacity to switch preventive maintenance to condition-based maintenance. That is, to monitor the actual condition of the wind turbine (WT) to decide when and which maintenance needs to be done. In particular, structural health monitoring (SHM) to monitor the foundation (support structure) condition is of utmost importance in offshore-fixed wind turbines. In this work a SHM strategy is presented to monitor online and during service a WT offshore jacket-type foundation. Standard SHM techniques, as guided waves with a known input excitation, cannot be used in a straightforward way in this particular application where unknown external perturbations as wind and waves are always present. To face this challenge, a vibration-response-only SHM strategy is proposed via machine learning methods. In this sense, the fractal dimension is proposed as a suitable feature to identify and classify different types of damage. The proposed proof-of-concept technique is validated in an experimental laboratory down-scaled jacket WT foundation undergoing different types of damage.
dc.language.isoeng
dc.rightsAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
dc.subject.lcshOffshore wind power plants
dc.subject.lcshStructural health monitoring
dc.subject.otherFractal dimension
dc.subject.otherStructural health monitoring
dc.subject.otherOffshore wind turbine
dc.subject.otherkNN
dc.subject.otherSupport vector machines
dc.titleDamage diagnosis for offshore wind turbine foundations based on the fractal dimension
dc.typeArticle
dc.subject.lemacParcs eòlics marins
dc.subject.lemacFractals
dc.subject.lemacMonitorització de salut estructural
dc.contributor.groupUniversitat Politècnica de Catalunya. CoDAlab - Control, Modelització, Identificació i Aplicacions
dc.identifier.doi10.3390/app10196972
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://creativecommons.org/licenses/by/4.0/
dc.rights.accessOpen Access
local.identifier.drac29509435
dc.description.versionPostprint (published version)
local.citation.authorHoxha, E.; Vidal, Y.; Pozo, F.
local.citation.publicationNameApplied sciences
local.citation.volume10
local.citation.number19
local.citation.startingPage6972:1
local.citation.endingPage6972:24


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Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain