Alarm Correlation to improve industrial fault management
Autor: | Anne Louis, Mohamed Amin Benatia, David Baudry |
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Rok vydání: | 2020 |
Předmět: |
Information management
0209 industrial biotechnology Decision support system Computer science 020208 electrical & electronic engineering 02 engineering and technology Root cause computer.software_genre Fault management Management information systems Identification (information) ALARM 020901 industrial engineering & automation Control and Systems Engineering Alarm management 0202 electrical engineering electronic engineering information engineering Data mining computer |
Zdroj: | IFAC-PapersOnLine. 53:10485-10492 |
ISSN: | 2405-8963 |
Popis: | Actual alarm systems used in manufacturing applications lacks explanation and indication of the root causes, which results in a poor decision making. In addition, manufacturing systems are more and more complex, so relaying on human operators for alarm information management becomes impossible. For this, a computerized tool to support human operators (i.E., decision support for information management system) is needed and would increase analytical capability for alarm analysis. To this effect, we introduce in this paper an autonomous data mining method to search historical alarm logs for the correlations that can represent causal relationships, which can support alarm management and system improvement. We investigate the use of Frequent Pattern Mining algorithm, an enumeration-tree based approach, for extracting relationships and automatically detect correlation between industrial alarms. Due to the time indexation of the alarm events, we adapt the algorithm in order to take into account the duration between alarms when extracting the itemsets. Filtered rules where evaluated according to the Minimmum support & Confidence framework. Obtained results show that FPM algorithm can derive very useful knowledge on system behaviour allowing the identification of alarm subsequence with the corresponding root cause. |
Databáze: | OpenAIRE |
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