Development of correlation-based pattern recognition algorithm and adaptive soft-sensor design

被引：32

作者：

Fujiwara, Koichi ^{[1
]}

Kano, Manabu ^{[1
]}

Hasebe, Shinji ^{[1
]}

机构：

[1] Kyoto Univ, Dept Chem Engn, Nishikyo Ku, Kyoto 6158510, Japan

来源：

CONTROL ENGINEERING PRACTICE | 2012年 / 20卷 / 04期

关键词：

Soft-sensor; Process observation and parameter; estimation; Just-In-Time modeling; Pattern recognition; Principal component analysis; PRINCIPAL COMPONENT ANALYSIS; SUPPORT VECTOR REGRESSION; LEAST-SQUARES REGRESSION; DISTILLATION COMPOSITIONS; SUBSPACE IDENTIFICATION; QUALITY; DIAGNOSIS;

D O I：

10.1016/j.conengprac.2010.11.013

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Although soft-sensors have been used for estimating product quality, they do not always function well due to not only changes in process characteristics but also the individual difference of production devices. Correlation-based Just-In-Time (CoJIT) modeling has been proposed to cope with such changes in process characteristics: however it cannot deal with the individual difference. In the present work, a new pattern recognition method, referred to as the nearest correlation (NC) method is proposed to cope with the individual difference. The proposed NC method is integrated with CoJIT modeling. The advantages of the proposed methods are demonstrated through a case study. (c) 2010 Elsevier Ltd. All rights reserved.

引用

页码：371 / 378

页数：8

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