文章基本信息

标题：Variable Selection for Fault Detection and Identification based on Mutual Information of Alarm Series ⁎
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作者：Matthieu Lucke ; Xueyu Mei ; Anna Stief 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2019
卷号：52
期号：1
页码：673-678
DOI：10.1016/j.ifacol.2019.06.140
语种：English
出版社：Elsevier
摘要：AbstractReducing the dimensionality of a fault detection and identification problem is often a necessity, and variable selection is a practical way to do it. Methods based on mutual information have been successful in that regard, but their applicability to industrial processes is limited by characteristics of the process variables such as their variability across fault occurrences. The paper introduces a new estimation strategy of mutual information criteria using alarm series to improve the robustness of the variable selection. The minimal-redundancy-maximal-relevance criterion on alarm series is suggested as new reference criterion, and the results are validated on a multiphase flow facility.
关键词：KeywordsFault detectiondiagnosisVariable selectionMutual information