Presentation Open Access

An innovative approach for failure diagnosis and prognosis for offshore wind turbines

Rodenas-Soler; González García


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  <identifier identifierType="DOI">10.5281/zenodo.3860345</identifier>
  <creators>
    <creator>
      <creatorName>Rodenas-Soler</creatorName>
      <affiliation>Cristian</affiliation>
    </creator>
    <creator>
      <creatorName>González García</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-3698-6284</nameIdentifier>
      <affiliation>Elena</affiliation>
    </creator>
  </creators>
  <titles>
    <title>An innovative approach for failure diagnosis and prognosis for offshore wind turbines</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>Diagnosis, Prognosis</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-06-18</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Text">Presentation</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3860345</alternateIdentifier>
  </alternateIdentifiers>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3860344</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/wesc2019</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;In the scope of the ROMEO project, an innovative approach is built in order to calculate automated values for diagnosis and prognosis. The physical approach to encapsule calculations into modules has been followed by two of the partners, feeding into a combination of Machine &amp;amp; Deep learning that would complete the assessment. This is an unique approach, of cost-effective techniques, that enable further stochastic studies (made probabilistic or risk-based diagnosis and prognosis) and easy to be implemented into service.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/745625/">745625</awardNumber>
      <awardTitle>Reliable OM decision tools and strategies for high LCoE reduction on Offshore wind</awardTitle>
    </fundingReference>
  </fundingReferences>
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