Ir al contenido (pulsa Retorno)

Universitat Politècnica de Catalunya

    • Català
    • Castellano
    • English
    • LoginRegisterLog in (no UPC users)
  • mailContact Us
  • world English 
    • Català
    • Castellano
    • English
  • userLogin   
      LoginRegisterLog in (no UPC users)

UPCommons. Global access to UPC knowledge

Banner header
69.147 UPC E-Prints
You are here:
View Item 
  •   DSpace Home
  • E-prints
  • Centres de recerca
  • CoDAlab - Control, Dades i Intel·ligència Artificial
  • Ponències/Comunicacions de congressos
  • View Item
  •   DSpace Home
  • E-prints
  • Centres de recerca
  • CoDAlab - Control, Dades i Intel·ligència Artificial
  • Ponències/Comunicacions de congressos
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Damage diagnosis for offshore fixed wind turbines

Thumbnail
View/Open
313-19-agis.pdf (1,201Mb)
 
10.24084/repqj16.200
 
  View UPCommons Usage Statistics
  LA Referencia / Recolecta stats
Includes usage data since 2022
Cita com:
hdl:2117/132097

Show full item record
Agis Cherta, DavidMés informacióMés informació
Vidal Seguí, YolandaMés informacióMés informacióMés informació
Pozo Montero, FrancescMés informacióMés informacióMés informació
Document typeConference report
Defense date2019
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
This work is protected by the corresponding intellectual and industrial property rights. Except where otherwise noted, its contents are licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
This paper proposes a damage diagnosis strategy to detect and classify different type of damages in a laboratory offshore-fixed wind turbine model. The proposed method combines an accelerometer sensor network attached to the structure with a conceived algorithm based on principal component analysis (PCA) with quadratic discriminant analysis (QDA). The paradigm of structural health monitoring can be undertaken as a pattern recognition problem (comparison between the data collected from the healthy structure and the current structure to diagnose given a known excitation). However, in this work, as the strategy is designed for wind turbines, only the output data from the sensors is used but the excitation is assumed unknown (as in reality is provided by the wind). The proposed methodology is tested in an experimental laboratory tower modeling an offshore-fixed jacked-type wind turbine. The obtained results show the reliability of the proposed approach
CitationAgis, D.; Vidal, Y.; Pozo, F. Damage diagnosis for offshore fixed wind turbines. A: International Conference on Renewable Energies and Power Quality. "Renewable Energy and Power Quality Journal (RE&PQJ): Tenerife, Spain: April 10-12, 2019". , p. 1-5. 
URIhttp://hdl.handle.net/2117/132097
DOI10.24084/repqj16.200
ISBN2172-038X
Other identifiershttp://www.icrepq.com/icrepq19/313-19-agis.pdf
Collections
  • CoDAlab - Control, Dades i Intel·ligència Artificial - Ponències/Comunicacions de congressos [200]
  • Departament de Matemàtiques - Ponències/Comunicacions de congressos [1.139]
  View UPCommons Usage Statistics

Show full item record

FilesDescriptionSizeFormatView
313-19-agis.pdf1,201MbPDFView/Open

Browse

This CollectionBy Issue DateAuthorsOther contributionsTitlesSubjectsThis repositoryCommunities & CollectionsBy Issue DateAuthorsOther contributionsTitlesSubjects

© UPC Obrir en finestra nova . Servei de Biblioteques, Publicacions i Arxius

info.biblioteques@upc.edu

  • About This Repository
  • Metadata under:Metadata under CC0
  • Contact Us
  • Send Feedback
  • Privacy Settings
  • Inici de la pàgina