DUGiDocsProcess diagnosis based on qualitative trend similarities using a sequence matching algorithm
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dc.date.accessioned
2017-05-31T08:14:12Z
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2017-05-31T08:14:12Z
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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
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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)
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Tots els drets reservats
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dc.title
Process diagnosis based on qualitative trend similarities using a sequence matching algorithm
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info:eu-repo/semantics/article
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info:eu-repo/semantics/embargoedAccess
dc.embargo.terms
Cap
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info:eu-repo/date/embargoEnd/2026-01-01
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info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
020424
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