文献类型：期刊文献

英文题名：Performance monitoring method based on balanced partial least square and Statistics Pattern Analysis

作者：Yang, Jian[1];Lv, Zheng[1];Shi, Hongbo[1];Tan, Shuai[1]

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

年份：2018

卷号：81

起止页码：121

外文期刊名：ISA TRANSACTIONS

收录：;EI(收录号：20183705808210);WOS:【SCI-EXPANDED(收录号:WOS:000449897700012)】；

语种：英文

外文关键词：Variable classification; Quality prediction; Performance monitoring; Statistics pattern analysis; Partial least square

摘要：For process monitoring, it's of significance to pay more attention to some performance indexes related to quality, economy or security. To this end, a novel performance monitoring method based on the prediction of the performance indexes is proposed in this paper to promote the efficiency of process monitoring. In this study, firstly, the process variables are classified into two categories according to the correlation with the performance indexes. Based on the two categories of variables, a balanced Partial Least Square algorithm is proposed by constructing an enhanced objective function to predict the performance indexes which cannot be measured online. Then, the prediction residual is modeled for monitoring via the Statistics Pattern Analysis to capture the variation in the performance indexes. Finally, two Simulink examples and a practical example are utilized for illustration and validation.