计算机应用研究2025,Vol.42Issue(1) :269-275.DOI:10.19734/j.issn.1001-3695.2024.01.0164

基于跨域因果图的FCC分馏系统攻击故障辨识方法

Discrimination between attacks and faults for FCC fractionation system with cross-domain causal diagram

杨晓雨 周纯杰 杜鑫
计算机应用研究2025,Vol.42Issue(1) :269-275.DOI:10.19734/j.issn.1001-3695.2024.01.0164

基于跨域因果图的FCC分馏系统攻击故障辨识方法

Discrimination between attacks and faults for FCC fractionation system with cross-domain causal diagram

杨晓雨 1周纯杰 1杜鑫1
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作者信息

  • 1. 华中科技大学人工智能与自动化学院,武汉 430074
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摘要

针对催化裂化(fluid catalytic cracking,FCC)分馏系统在网络攻击和系统故障具有相似特征情况下难以辨识的问题,提出了一种基于跨域因果图的攻击故障辨识方法.首先,将数据驱动和拓扑知识融合以构建跨域因果图,涵盖物理层和信息层的变量节点和设备节点;其次,结合多源异常证据集,设计了基于弗洛伊德的异常因果传播路径搜索算法,得到异常节点间的因果传播路径;最后根据必经点约束、单点异常约束、必经点最大数量约束等条件,结合异常发生时间,得到异常传播路径的最小树型图,根据根节点位置判断系统异常类型.该方法在FCC分馏仿真系统上验证了有效性,结果表明其辨识准确率为94.84%,对正常工况、故障工况和攻击工况的检测召回率分别为97.11%、93.25%、95.30%,相比同类方案,该方法不仅解决了相似特征带来的辨识难题,还能在保证较高的辨识准确率的同时,给出异常传播路径,为安全防护提供报警信息.

Abstract

To solve the problem that attacks had similar characteristics like faults in physical data,this paper proposed a dis-crimination method,with cross-domain causal diagram,between attacks and faults for FCC fractionation system.Firstly,the process of cross-domain causal graph construction integrated data-driven method and topological knowledge method,covering the physical layer and information layer.Secondly,combined with the multi-source anomaly evidence,this paper presented a causal path search method based on Floyd algorithm to obtain the causal paths between abnormal nodes.Finally it obtained the minimum fork tree of the anomaly propagation path according to the dominators constraint,the single point anomaly constraint,the maximum number constraint of dominators,along with the occurrence time of abnormal nodes.This method determined the root cause of anomaly according to the position of the root node.The test on a simulated FCC fractionation system validated the effectiveness of the proposed method.The results show that the identification accuracy of this method is 94.84%,and the recall rates of normal,fault and attack conditions are 97.11%,93.25%and 95.30%.Compared with similar schemes,this method not only solves the identification problems caused by similar features,but also provides the abnormal propagation path and pro-vides alarm information for security protection while ensuring high identification accuracy.

关键词

跨域因果图/路径搜索/最小树型图/攻击故障辨识/催化裂化

Key words

cross-domain causal diagram/path search/minimum fork tree/attacks and faults identification/fluid catalytic cracking

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出版年

2025
计算机应用研究
四川省电子计算机应用研究中心

计算机应用研究

CSTPCDCSCD北大核心
影响因子:0.93
ISSN:1001-3695
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