Name
Title | ||
|---|---|---|
Concurrent PLS-based process monitoring with incomplete input and quality measurements. |
Abstract | ||
|---|---|---|
The process monitoring based on concurrent partial least square (CPLS) performs well on the monitoring of input and quality variables through five monitoring statistics. However, in practice, the case of missing variable is very common and the incomplete measurements will make it difficult to implement this monitoring method. Considering the presence of missing measurements occurring in both input and quality variables, this paper analyzes the influence of missing measurements on monitoring performance based on the assumption that input and quality variables satisfy multivariate Gaussian distribution under normal operation. The proposed method estimates the conditional distributions of missing variables, scores and residuals given the observable variables, and denotes monitoring statistics with these conditional distributions. Then, the probabilistic uncertain ranges of monitoring statistics are derived by calculating the general quadratic formulations of Gaussian-distributed missing variables. To determine the process operation in the presence of missing variables, the proposed method employs these uncertain ranges as monitoring statistics. Simulation examples illustrate feasibility of this proposed method and demonstrate its effectiveness. (C) 2014 Elsevier Ltd. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.compchemeng.2014.03.022 | Computers & Chemical Engineering |
Keywords | DocType | Volume |
Process monitoring,CPLS,Incomplete measurement,Monitoring statistic | Journal | 67 |
ISSN | Citations | PageRank |
0098-1354 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhong-Gai Zhao | 1 | 0 | 0.68 |
| Qing-Hua Li | 2 | 1563 | 88.15 |
| Min Huang | 3 | 0 | 0.34 |
| Fei Liu | 4 | 76 | 10.80 |