Improved alarm flood analysis by cluster identification and alarm assignment

Feras El Sakka, Henry Bloch, Jakob Kinghorst, Mina Fahimi Pirehgalin, Alexander Fay, Birgit Vogel-Heuser

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Alarm analysis aims to group similar and frequently occurring alarm sequences in alarm clusters. These clusters are so far identified by data-driven approaches based on the historical alarm data. To improve the alarm analysis, especially the handling of alarm floods, additional information can be integrated into state of the art alarm analysis approaches. This additional information consists of plant and process information, which improves the identification and detection of alarm clusters. Information such as neighborly relations of alarm sources or the heat transmission between two not directly connected alarm sources, improve the identification of alarm clusters. The handling of unknown alarms, which occur during runtime, and the assignment to known alarms and additionally to identified alarm clusters can be supported by process and plant information as well. Based on the combination of alarm analysis approaches and the evaluation of process and plant information, it seems feasible to identify causal coherent alarms within alarm floods. This improvement supports the plant operator to handle the abnormal situation by a reduction of the occurring alarms and information about the causal relations between alarms.

Original languageEnglish
Pages (from-to)647-655
Number of pages9
JournalAt-Automatisierungstechnik
Volume66
Issue number8
DOIs
StatePublished - 28 Aug 2018

Keywords

  • Alarm sequence analysis
  • alarm cluster detection
  • causality analysis
  • plant information sources
  • process information sources

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