Process diagnosis based on qualitative trend similarities using a sequence matching algorithm
dc.contributor.author
dc.date.accessioned
2017-05-31T08:14:12Z
dc.date.available
2017-05-31T08:14:12Z
dc.date.issued
2014-09
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0959-1524
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dc.description.abstract
This paper focuses on process diagnosis based on symptoms described by qualitative trends extracted from signals. Main contributions are a new similarity algorithm between qualitative sequences and a generalised approach for on-line diagnosis based on that similarity measure. Process situations are identified by converting sensor time series into qualitative sequences and comparing them with those corresponding to known faulty states. Performance of this approach has been evaluated on line in a steam generator plant
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This work has been supported by the research project DPI2009-07891 funded by the Spanish Government
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application/pdf
dc.language.iso
eng
dc.publisher
Elsevier
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info:eu-repo/grantAgreement/MICINN//DPI2009-07891/ES/Monitorizacion Inteligente De La Calidad De La Energia Electrica/
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Reproducció digital del document publicat a: http://dx.doi.org/10.1016/j.jprocont.2014.06.010
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© Journal of Process Control, 2014, vol. 24, núm. 9, p. 1412-1424
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Articles publicats (D-EEEiA)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Process diagnosis based on qualitative trend similarities using a sequence matching algorithm
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/embargoedAccess
dc.embargo.terms
Cap
dc.date.embargoEndDate
info:eu-repo/date/embargoEnd/2026-01-01
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
020424
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