文献类型：期刊文献

英文题名：Data-Driven Distributed Local Fault Detection for Large-Scale Processes Based on the GA-Regularized Canonical Correlation Analysis

作者：Jiang, Qingchao[1,2];Ding, Steven X.[3];Wang, Yang[4,5];Yan, Xuefeng[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Univ Duisburg Essen, Inst Automat Control & Complex Syst AKS, D-47057 Duisburg, Germany;[3]Univ Duisburg Essen, Inst Automat Control & Complex Syst, D-47057 Duisburg, Germany;[4]Shanghai Dianji Univ, Sch Elect Engn, Shanghai 200240, Peoples R China;[5]Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200072, Peoples R China

年份：2017

卷号：64

期号：10

起止页码：8148

外文期刊名：IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

收录：;EI(收录号：20174004225331);WOS:【SCI-EXPANDED(收录号:WOS:000410160200052)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61603138, in part by the Fundamental Research Funds for the Central Universities under Grant 222201717006 and Grant 222201714027, in part by the Young Teacher Study Abroad Program of Shanghai under Grant A1-0217-16-003-01, and in part by the Alexander von Humboldt Foundation.

语种：英文

外文关键词：Canonical correlation analysis (CCA); distributed fault detection; genetic algorithm (GA); large-scale processes

摘要：Large-scale processes have become common, and fault detection for such processes is imperative. This work studies the data-driven distributed local fault detection problem for large-scale processes with interconnected subsystems and develops a genetic algorithm (GA)-regularized canonical correlation analysis (CCA)-based distributed local fault detection scheme. For each subsystem, the GA-regularized CCA is first performed with its all coupled systems, which aims to preserve the maximum correlation with the minimal communication cost. A CCA-based residual is then generated, and corresponding statistic is constructed to achieve optimal fault detection for the subsystem. The distributed fault detector performs local fault detection for each subsystem using its own measurements and the information provided by its coupled subsystems and therefore exhibits a superior monitoring performance. The regularized CCA-based distributed fault detection approach is tested on a numerical example and the Tennessee Eastman benchmark process. Monitoring results indicate the efficiency and feasibility of the proposed approach.