Show simple item record

dc.contributor.authorHoell, Simon
dc.contributor.authorOmenzetter, Piotr
dc.contributor.editorMeyendorf, Norbert G.
dc.date.accessioned2017-09-12T11:00:37Z
dc.date.available2017-09-12T11:00:37Z
dc.date.issued2017-04-19
dc.identifier.citationHoell , S & Omenzetter , P 2017 , Optimal statistical damage detection and classification in an experimental wind turbine blade using minimum instrumentation . in N G Meyendorf (ed.) , Smart Materials and Nondestructive Evaluation for Energy Systems 2017 . vol. 10171 , 101710D , SPIE , Smart Materials and Nondestructive Evaluation for Energy Systems 2017 , Portland , United States , 27-28 March . DOI: 10.1117/12.2257228en
dc.identifier.citationconferenceen
dc.identifier.isbn9781510608276
dc.identifier.otherPURE: 104835175
dc.identifier.otherPURE UUID: 244de867-b5b9-47b4-9e6e-cf54bfded606
dc.identifier.otherScopus: 85021821176
dc.identifier.urihttp://www.scopus.com/inward/record.url?scp=85021821176&partnerID=8YFLogxKen
dc.identifier.urihttp://hdl.handle.net/2164/9287
dc.format.extent12en
dc.language.isoeng
dc.publisherSPIE
dc.relation.ispartofSmart Materials and Nondestructive Evaluation for Energy Systems 2017en
dc.rightsCopyright 2017 Society of Photo-Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.en
dc.subjectDamage classificationen
dc.subjectPrincipal component analysisen
dc.subjectStatistical classificationen
dc.subjectTime series methodsen
dc.subjectVibration analysisen
dc.subjectWind turbinesen
dc.subjectTA Engineering (General). Civil engineering (General)en
dc.subjectElectronic, Optical and Magnetic Materialsen
dc.subjectCondensed Matter Physicsen
dc.subjectComputer Science Applicationsen
dc.subjectApplied Mathematicsen
dc.subjectElectrical and Electronic Engineeringen
dc.subject.lccTAen
dc.titleOptimal statistical damage detection and classification in an experimental wind turbine blade using minimum instrumentationen
dc.typeBook itemen
dc.contributor.institutionUniversity of Aberdeen, School of Engineering, Engineeringen
dc.contributor.institutionUniversity of Aberdeen, Energyen
dc.contributor.institutionUniversity of Aberdeen, Engineeringen
dc.description.statusPeer revieweden
dc.description.versionPostprinten
dc.identifier.doihttp://dx.doi.org/10.1117/12.2257228


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record