期刊
JOURNAL OF PROCESS CONTROL
卷 19, 期 5, 页码 816-826出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jprocont.2008.11.001
关键词
Batch process; Multivariate statistical process control; PCA; Process modeling; Process monitoring; Multiphase; Multistage
资金
- Hong Kong Research Grant Council [613017]
Multiple phases/stages with transitions from phase to phase are important characteristics of many batch processes. In order to model and monitor batch processes more accurately and efficiently, such process features are needed to be considered carefully. In this work, an index based on the angles between different principal component analysis (PCA) score spaces is developed to quantify the similarities between PCA models. Phase division algorithm is designed based on this new PCA similarity index, following by a statistical transition identification step. The steady phase ranges and transition ranges are then modeled separately. The transition models can be calculated by solving the optimization problems. Application examples show the advantages of the proposed method on both batch process modeling and online monitoring. (C) 2008 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据