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dc.contributor.authorAftab, Muhammad Faisal
dc.contributor.authorHovd, Morten
dc.contributor.authorSivalingam, Selvanathan
dc.date.accessioned2019-05-03T11:20:29Z
dc.date.available2019-05-03T11:20:29Z
dc.date.created2018-11-29T16:00:22Z
dc.date.issued2018
dc.identifier.citationComputers and Chemical Engineering. 2018, 117 320-330.nb_NO
dc.identifier.issn0098-1354
dc.identifier.urihttp://hdl.handle.net/11250/2596450
dc.description.abstractPlant-wide oscillation detection is an important task in the maintenance of large-scale industrial control systems, owing to the fact that in an interactive multi-loop environment oscillation generated in one loop may propagate to the different parts of the plant. In such a scenario, it is required that different loops oscillating due to a common cause and hence similar frequency may be grouped together. In this paper an adaptive method for plant-wide oscillation detection based on multivariate empirical mode decomposition (MEMD) along with a grouping algorithm is proposed. The method can identify multiple oscillation groups among different variables as well as variables with random noise only. The proposed method is also applicable to both non-linear and non-stationary time series where the techniques based on the conventional Fourier analysis are prone to errors. Within each group that oscillate due to a common cause, the method can also indicate the location of the probable root cause of oscillations. The efficacy of the proposed method is established with the help of both simulation and industrial case studies.nb_NO
dc.language.isoengnb_NO
dc.publisherElseviernb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titlePlant-wide oscillation detection using multivariate empirical mode decompositionnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber320-330nb_NO
dc.source.volume117nb_NO
dc.source.journalComputers and Chemical Engineeringnb_NO
dc.identifier.doi10.1016/j.compchemeng.2018.06.007
dc.identifier.cristin1637114
dc.description.localcode© 2018. This is the authors’ accepted and refereed manuscript to the article. Locked until 15.6.2020 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/nb_NO
cristin.unitcode194,63,25,0
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode2


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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