Identification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach

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dc.contributor.authorTRIGO, F. C.
dc.contributor.authorMARTINS, F. P. R.
dc.contributor.authorFLEURY, A. T.
dc.contributor.authorSILVA JUNIOR, H. C.
dc.date.accessioned2022-01-12T22:00:40Z
dc.date.available2022-01-12T22:00:40Z
dc.date.issued2014-02-03
dc.description.abstractAbstract Aiming at overcoming the difficulties derived from the traditional camera calibration methods to record the underwater environment of a towing tank where experiments of scaled-model risers are carried on, a computer vision method, combining traditional image processing algorithms and a self-calibration technique was implemented. This method was used to identify the coordinates of control-points viewed on a scaled-model riser submitted to a periodic force applied to its fairlead attachment point. To study the observed motion, the riser was represented as a pseudo-rigid body model (PRBM) and the hypotheses of compliant mechanisms theory were assumed in order to cope with its elastic behavior. The derived Lagrangian equations of motion were linearized and expressed as a state-space model in which the state variables include the generalized coordinates and the unknown generalized forces. The state-vector thus assembled is estimated through a Kalman Filter. The estimation procedure allows the determination of both the generalized forces and the tension along the cable, with statistically proven convergence. © 2013 Elsevier Ltd. All rights reserved.
dc.description.firstpage124
dc.description.issuenumber1-2
dc.description.lastpage140
dc.description.volume43
dc.identifier.citationTRIGO, F. C.; MARTINS, F. P. R.; FLEURY, A. T.; SILVA JUNIOR, H. C. Identification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach. Mechanical Systems and Signal Processing, v. 43, n. 1-2, p. 124-140, feb. 2014.
dc.identifier.doi10.1016/j.ymssp.2013.10.005
dc.identifier.issn0888-3270
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/4015
dc.relation.ispartofMechanical Systems and Signal Processing
dc.rightsAcesso Restrito
dc.subject.otherlanguageCompliant mechanisms
dc.subject.otherlanguageComputer vision
dc.subject.otherlanguageKeywords
dc.subject.otherlanguageNon-linear adaptive Kalman filter
dc.subject.otherlanguageRiser dynamics
dc.subject.otherlanguageShaping filter
dc.titleIdentification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach
dc.typeArtigo
fei.scopus.citations15
fei.scopus.eid2-s2.0-84889097263
fei.scopus.subjectAdaptive kalman filter
fei.scopus.subjectImage processing algorithm
fei.scopus.subjectKeywords
fei.scopus.subjectPseudo-rigid body models
fei.scopus.subjectRiser dynamics
fei.scopus.subjectSelf-calibration techniques
fei.scopus.subjectShaping filters
fei.scopus.subjectUnderwater environments
fei.scopus.updated2024-07-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84889097263&origin=inward
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