Volume 17, Issue 2 (Journal of Control, V.17, N.2 Summer 2023)
JoC 2023, 17(2): 113-127 |
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Roohi M H, Izadi I. A review of alarm flood analysis methods in industrial processes: pattern recognition and similarity analysis. JoC 2023; 17 (2) :113-127
URL: http://joc.kntu.ac.ir/article-1-1005-en.html
URL: http://joc.kntu.ac.ir/article-1-1005-en.html
1- Isfahan University of Technology
Abstract: (1852 Views)
In this paper, recently proposed methods of pattern recognition and similarity analysis in alarm management systems are reviewed, and the impact of these methods on improving the efficiency of these systems, with emphasis on alarm floods, is discussed. Various types of alarms and their patterns are analyzed, highlighting the potential for more precise predictions, timely response strategies, and improvements in system maintenance. The technological advancements that have strengthened these methods are explained. More specifically, the role of recent advancements in artificial intelligence and machine learning in enhancing pattern recognition and similarity analysis, especially during alarm floods, is studied. The combination of these modern technologies with traditional alarm management systems paves the way for significant improvements in industrial safety. Examples from various industries are provided to demonstrate the practical application and impact of these methods.
Keywords: Alarm management systems, Alarm flood, Pattern recognition, Similarity analysis, Industrial safety.
Type of Article: Research paper |
Subject:
New approaches in control engineering
Received: 2023/08/27 | Accepted: 2023/09/11 | ePublished ahead of print: 2023/09/17 | Published: 2023/09/21
Received: 2023/08/27 | Accepted: 2023/09/11 | ePublished ahead of print: 2023/09/17 | Published: 2023/09/21
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