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dc.contributor.authorAizpurúa, Omar
dc.contributor.authorCaballero, Rony
dc.contributor.authorGalán, Ramón
dc.contributor.authorJiménez, Agustín
dc.date.accessioned2017-08-01T20:51:50Z
dc.date.accessioned2017-08-01T20:51:50Z
dc.date.available2017-08-01T20:51:50Z
dc.date.available2017-08-01T20:51:50Z
dc.date.issued2009-07-01
dc.date.issued2009-07-01
dc.identifier.urihttp://ridda2.utp.ac.pa/handle/123456789/2412
dc.identifier.urihttp://ridda2.utp.ac.pa/handle/123456789/2412
dc.descriptionThe paper presents a methodology that integrates several available techniques to manage the massive amount of alarm signals in electrical power dispatch control centers, as well as the contribution of each entity involved in the systems. Artificial intelligence techniques that can be used to solve this problem are reviewed here. The final objective is to find the root cause of avalanches of alarms (failure trees) and to reduce their number through grouping or clustering techniques, complying with the EEMUA 191 standards. Even though other contributions in this topic have been made before, the alarm management problem continues to be practically unsolved for many applications in industry. Here, the integration is developed using the ontology of the alarms. Additionally, in this methodology, a rule based expert systems is used to find the "Alarm Root Cause" and Clustering Technique (data segmentation) approach to treat the historical database of alarms.en_US
dc.description.abstractThe paper presents a methodology that integrates several available techniques to manage the massive amount of alarm signals in electrical power dispatch control centers, as well as the contribution of each entity involved in the systems. Artificial intelligence techniques that can be used to solve this problem are reviewed here. The final objective is to find the root cause of avalanches of alarms (failure trees) and to reduce their number through grouping or clustering techniques, complying with the EEMUA 191 standards. Even though other contributions in this topic have been made before, the alarm management problem continues to be practically unsolved for many applications in industry. Here, the integration is developed using the ontology of the alarms. Additionally, in this methodology, a rule based expert systems is used to find the "Alarm Root Cause" and Clustering Technique (data segmentation) approach to treat the historical database of alarms.en_US
dc.languageeng
dc.language.isoengen_US
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectmassive alarmen_US
dc.subjectpower administrationen_US
dc.subjectmassive alarm
dc.subjectpower administration
dc.titleA New Methodology for Massive Alarm Management System in Electrical Power Administrationen_US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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