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A Causal Fusion inference Method for Industrial Alarm Root Cause Analysis Based on Process Topology and Alarm Event Data

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Journal of Beijing Institute of Technology 2022年第4期31卷 371-381页

作者： Pan Zhang Wenkai Hu Xiangxiang Zhang Jianqi An School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China

Modern industrial systems are usually in large scale,consisting of massive components and variables that form a complex system *** to the interconnections among devices,a fault may occur and propagate to exert widespread influences and lead to a variety of *** the root causes of alarms is beneficial to the decision supports in making corrective alarm *** data-driven methods for alarm root cause analysis detect causal relations among alarms mainly based on historical alarm event *** improve the accuracy,this paper proposes a causal fusion inference method for industrial alarm root cause analysis based on process topology and alarm events.A Granger causality inference method considering process topology is exploited to find out the causal relations among *** topological nodes are used as the inputs of the model,and the alarm causal adjacency matrix between alarm variables is obtained by calculating the likelihood of the topological Hawkes *** root cause is then obtained from the directed acyclic graph(DAG)among alarm *** effectiveness of the proposed method is verified by simulations based on both a numerical example and the Tennessee Eastman process(TEP)model.

关键词： roots cause analysis causality inference process topology alarm events

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