مروری بر روش ‌های تحلیل هجوم هشدار در فرآیندهای صنعتی: شناسایی الگو و بررسی شباهت

ﺩﺭ ﺍﻳﻦ ﻣﻘﺎﻟﻪ، ﻣﺮﻭﺭ ﺭﻭﺵ ﻫﺎی ﻣﺨﺘﻠﻒ ﺷﻨﺎﺳﺎیی ﺍﻟﮕﻮ ﻭ ﺗﺠﺰﻳﻪ ﻭ ﺗﺤﻠﻴﻞ ﺷﺒﺎﻫﺖ ﺩﺭ ﺳﻴﺴﺘﻢﻫﺎی ﻫﺸﺪﺍﺭ ﻭ ﺗﺎﺛﻴﺮ ﺍﻳﻦ ﺭﻭﺵﻫﺎ ﺩﺭ ﺑﻬﺒﻮﺩ ﻛﺎﺭﺍیی ﺍﻳﻦ ﺳﻴﺴﺘﻢﻫﺎ، با تمرکز بر هجوم هشدار ﺍﺭﺍﺋﻪ ﺧﻮﺍﻫﺪ ﺷﺪ. ﺑﺎ ﺗﺠﺰﻳﻪ ﻭ ﺗﺤﻠﻴﻞ ﺍﻧﻮﺍﻉ ﻣﺨﺘﻠﻒ ﻫﺸﺪﺍﺭﻫﺎ ﻭ ﺍﻟﮕﻮﻫﺎی ﺁﻧﻬﺎ، ﺍﻣﻜﺎﻥ ﭘﻴﺶ بینی ﻫﺎی ﺩﻗﻴﻖﺗﺮ، ﻭﺍﻛﻨﺶ ﺑﻪ ﻣﻮﻗﻊ ﻭ ﺑﻬﺒﻮﺩ ﻧﮕﻬﺪﺍﺭی ﺳﻴﺴﺘﻢ ﻓﺮﺍﻫﻢ می ﺷﻮﺩ. ﻫﻤﭽﻨﻴﻦ ﺩﺭ ﺍﻳﻦ ﻣﻘﺎﻟﻪ ﺑﻪ ﭘﻴﺸﺮﻓﺖﻫﺎی ﺍﺧﻴﺮ ﻓﻨﺎﻭﺭی ﻛﻪ ﺍﻳﻦ ﺭﻭﺵﻫﺎ ﺭﺍ ﺗﻘﻮﻳﺖ ﻛﺮﺩﻩﺍﻧﺪ ﺍﺷﺎﺭﻩ ﻣﻲﺷﻮﺩ. ﺑﻪ ﻃﻮﺭ ﺧﺎﺹ ﻧﻘﺶ ﭘﻴﺸﺮﻓﺖﻫﺎی ﺍﺧﻴﺮ ﺩﺭ ﺣﻮﺯﻩ ﻫﻮﺵ ﻣﺼﻨﻮعی ﻭ ﻳﺎﺩﮔﻴﺮی ﻣﺎﺷﻴﻦ ﺩﺭ ﺑﻬﺒﻮﺩ ﺭﻭﺵﻫﺎی ﺷﻨﺎﺳﺎیی ﺍﻟﮕﻮ ﻭ ﺗﺠﺰﻳﻪ ﻭ ﺗﺤﻠﻴﻞ ﺷﺒﺎﻫﺖ به ویژه در زمان هجوم هشدار ﺑﺮﺭﺳﻲ ﺧﻮﺍﻫﺪ ﺷﺪ. ﺍﺳﺘﻔﺎﺩﻩ ﺍﺯ ﺍﻳﻦ ﻓﻨﺎﻭﺭی ﻫﺎی ﻧﻮﻳﻦ در ﺳﻴﺴﺘﻢﻫﺎی ﻣﺪﻳﺮﻳﺖ ﻫﺸﺪﺍﺭ ﺳﻨتی ﺭﺍﻩ ﺭﺍ ﺑﺮﺍﻱ ﺑﻬﺒﻮﺩ ﻗﺎﺑﻞ ﺗﻮﺟﻪ ﺩﺭ ﺍﻳﻤنی ﺻﻨﻌتی ﻫﻤﻮﺍﺭ می ﻛﻨﺪ. ﺩﺭ ﺍﻳﻦ ﺭﺍﺳﺘﺎ ﻧﻤﻮﻧﻪﻫﺎیی ﺍﺯ ﺻﻨﺎﻳﻊ ﻣﺨﺘﻠﻒ ﺑﺮﺍی ﻣﺸﺨﺺ ﺷﺪﻥ ﻛﺎﺭﺑﺮﺩ ﻋﻤلی ﻭ ﺗﺄﺛﻴﺮ ﺍﻳﻦ ﺭﻭﺵ ﻫﺎ ﻋﻨﻮﺍﻥ ﺧﻮﺍﻫﺪ ﺷﺪ.

a review of alarm flood analysis methods in industrial processes: pattern recognition and similarity analysis

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.