文献类型：会议论文

英文题名：Process Monitoring Based on Performance-Triggered Scheme

作者：Zhang, Ming-shan[1];Yang, Jian[1];Tan, Shuai[1];Shi, Hong-bo[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China

会议论文集：10th IFAC Symposium on Advanced Control of Chemical Processes (ADCHEM)

会议日期：JUL 25-27, 2018

会议地点：Shenyang, PEOPLES R CHINA

语种：英文

外文关键词：process monitoring; fault detection; variable selection; dictionary learning; low rank representation

摘要：In process monitoring, some specific performance indexes need to be paid attention to. Therefore, the performance-triggered process monitoring scheme is proposed. Different from the traditional process monitoring method, the process is considered normal if there is no apparent anomaly happens on the performance index. In order to predict the values of performance indexes that cannot be measured in real time, ridge regression is used. And, the regression coefficients are used to pick the most relevant process variables for subsequent modelling. In this scheme, after the performance index exceeds the control limit, the monitoring of the relevant process variables is triggered to determine whether the prediction is abnormal due to the occurrence of a fault. Then, dictionary learning method and Low rank representation (LRR) are used for feature extraction and construction of the statistic. Finally, the effectiveness of the proposed method is verified by a numerical example and the Tennessee Eastman (TE) process. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.