Systematic rationalization approach for multivariate correlated alarms based on interpretive structural modeling and Likert scale  

基于解释结构模型与李克特量表的多变量关联报警的系统合理化方法（英文）

作　　者：高慧慧 徐圆 顾祥柏 林晓勇 朱群雄 

机构地区：[1]College of Information Science & Technology,Beijing University of Chemical Technology [2]Engineering Research Center of Intelligent PSE,Ministry of Education in China [3]Sinopec Engineering (Group) Co.,LTD

出　　处：《Chinese Journal of Chemical Engineering》2015年第12期1987-1996,共10页中国化学工程学报（英文版）

基　　金：Supported by the National Natural Science Foundation of China(61473026,61104131);the Fundamental Research Funds for the Central Universities(JD1413)

摘　　要：Alarm flood is one of the main problems in the alarm systems of industrial process. Alarm root-cause analysis and alarm prioritization are good for alarm flood reduction. This paper proposes a systematic rationalization method for multivariate correlated alarms to realize the root cause analysis and alarm prioritization. An information fusion based interpretive structural model is constructed according to the data-driven partial correlation coefficient calculation and process knowledge modification. This hierarchical multi-layer model is helpful in abnormality propagation path identification and root-cause analysis. Revised Likert scale method is adopted to determine the alarm priority and reduce the blindness of alarm handling. As a case study, the Tennessee Eastman process is utilized to show the effectiveness and validity of proposed approach. Alarm system performance comparison shows that our rationalization methodology can reduce the alarm flood to some extent and improve the performance.Alarm flood is one of the main problems in the alarm systems of industrial process. Alarm root-cause analysis and alarm prioritization are good for alarm flood reduction. This paper proposes a systematic rationalization method for multivariate correlated alarms to realize the root cause analysis and alarm prioritization. An information fusion based interpretive structural model is constructed according to the data-driven partial correlation coefficient calculation and process knowledge modification. This hierarchical multi-layer model is helpful in abnormality propagation path identification and root-cause analysis. Revised Likert scale method is adopted to determine the alarm priority and reduce the blindness of alarm handling. As a case study, the Tennessee Eastman process is utilized to show the effectiveness and validity of proposed approach. Alarm system performance comparison shows that our rationalization methodology can reduce the alarm flood to some extent and improve the performance.

关 键 词：Alarm rationalization Root-cause analysis Alarm priority Interpretive structural modeling Likert scale Tennessee Eastman process 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置] N94[自动化与计算机技术—控制科学与工程]