This work presents a novel method for inferring causal dependencies among abnormal behaviours of components in Complex Technical Infrastructures (CTIs) from large-scale databases of alarm messages. The proposed method extracts causal relationships from association rules performing a probabilistic analysis of the alarm occurrence times and applying a modified version of the quicksort algorithm. Its capability and effectiveness is illustrated by application to a real large-scale databases of alarm messages collected in the technical infrastructure of the European Organization for Nuclear Research (CERN).

A method for inferring casual dependencies among abnormal behaviours of components in complex technical infrastructures

Antonello F.;Baraldi P.;Zio E.;
2020

Abstract

This work presents a novel method for inferring causal dependencies among abnormal behaviours of components in Complex Technical Infrastructures (CTIs) from large-scale databases of alarm messages. The proposed method extracts causal relationships from association rules performing a probabilistic analysis of the alarm occurrence times and applying a modified version of the quicksort algorithm. Its capability and effectiveness is illustrated by application to a real large-scale databases of alarm messages collected in the technical infrastructure of the European Organization for Nuclear Research (CERN).
30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM 2020
Alarms
Association rules
Causality
Complex technical infrastructures
Dependent abnormal behaviours
Quicksort algorithm
Time-Dependent analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1181268
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