Online Alarm Flood Classification Using Alarm Coactivations Article Swipe
Matthieu Lucke
,
Moncef Chioua
,
Chriss Grimholt
,
Martin Hollender
,
Nina F. Thornhill
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.1407660
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.1407660
Alarms indicate abnormal operation of the process plants and alarm floods constitute specific abnormal episodes that cannot be handled safely by the operators. In that regard, online alarm flood classification based on a bank of past historical episodes provides support on how to handle ongoing alarm sequences. This paper introduces a new approach based on alarm coactivations that is appropriate for the analysis of ongoing sequences. The method shows improvements when compared to an established sequence alignment approach for abnormal episode analysis of a gas oil separation plant.
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- https://zenodo.org/record/1407660
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://doi.org/10.5281/zenodo.1407660Digital Object Identifier
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Online Alarm Flood Classification Using Alarm CoactivationsWork title
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paratextOpenAlex work type
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enPrimary language
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2018Year of publication
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2018-07-25Full publication date if available
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Matthieu Lucke, Moncef Chioua, Chriss Grimholt, Martin Hollender, Nina F. ThornhillList of authors in order
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https://zenodo.org/record/1407660Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://zenodo.org/record/1407660Direct OA link when available
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ALARM, Computer science, Flood myth, Artificial intelligence, Engineering, Geography, Electrical engineering, ArchaeologyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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