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作 者:李元[1] 章展鹏 徐鸣远[1] 陈丙珍[1] 赵劲松[1]
机构地区:[1]化学工程联合国家重点实验室(清华大学),北京100084
出 处:《化工学报》2015年第8期3153-3160,共8页CIESC Journal
基 金:国家高技术研究发展计划项目(2013AA040702);国家自然科学基金项目(61433001)~~
摘 要:报警管理在化工过程安全中具有重要地位,而报警相关性挖掘是报警管理的重要组成部分。在传统的基于凝聚层次聚类的报警相关性挖掘方法基础上,提出非规整报警相关性计算方法,弥补了传统方法难以处理延迟时间变化与非对称情况的不足。同时以概率形式表示相关性大小,使不同位点之间的相关性计算结果具有可比性。经过仿真案例与工厂真实生产案例测试,该方法能够有效挖掘过程中出现的报警相关性,进而指导报警系统合理化。Alarm correlation mining is a key part of alarm management which plays an important role for chemical process safety. According to the traditional alarm correlation mining algorithms which is based on hierarchical clustering schemes, this paper proposed a non-regular alarm correlation calculation method to make up the deficiency that the traditional algorithms have, in dealing with the situation of delayed time change and asymmetry of alarms. Moreover, the value of alarm correlation was determined in the form of probability, which made the alarm correlation among different tags comparable. Furthermore, case studies based on simulation and real industrial process data were performed to demonstrate the effectiveness of the proposed methods in mining alarm correlation.
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