Distributed data-driven fault detection for industrial interconnected systems with unknown topology structure

被引：0
作者：
Gao, Jingjing [1 ]
Yang, Xu [1 ]
Zhou, Xian [2 ]
Li, Qing [1 ]
Huang, Jian [1 ]
Cui, Jiarui [1 ]
机构：
[1] Univ Sci & Technol Beijing, Key Lab Knowledge Automat Ind Proc, Minist Educ, Sch Automat & Elect Engn, Beijing, Peoples R China
[2] Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing, Peoples R China
来源：
IFAC PAPERSONLINE | 2024年 / 58卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Fault detection; industrial interconnected systems; subspace identification method; gap metric; data-driven;
D O I：
10.1016/j.ifacol.2024.07.296
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Driven by the enhancing requirements for ensuring stable operation of complex industrial processes, this paper investigates a distributed data-driven fault detection (FD) method for industrial interconnected systems. The topology structure of the industrial interconnected system is presumed to be unknown. To this end, the input/output (I/O) data-set model for the interconnected system and the distributed input/output data-set models for the subsystems are derived first. Then, the topology structure of the interconnected system is reconstructed through data-driven realization of gap metric by utilizing the subspace identification method. Subsequently, the distributed data-driven fault detection method with enhanced information exchange topology is developed. Finally, we validate the feasibility and efficiency of the proposed method by conducting a case study on a chemical process consisting of four continuous-stirred tank reactors (CSTRs). Copyright (c) 2024 The Authors.
引用
收藏
页码：670 / 675
页数：6
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