First-Principles Model Diagnosis in Batch Systems by Multivariate Statistical Modeling

被引：0

作者：

Meneghetti, Natascia ^{[1
]}

Facco, Pierantonio ^{[1
]}

Bermingham, Sean ^{[2
]}

Slade, David ^{[2
]}

Bezzo, Fabrizio ^{[1
]}

Barolo, Massimiliano ^{[1
]}

机构：

[1] Univ Padua, Dept Ind Engn, CAPE Lab, I-35131 Padova PD, Italy

[2] PSE Proc Syst Enterprise Ltd, London W6 7HA, England

来源：

12TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING (PSE) AND 25TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING (ESCAPE), PT A | 2015年 / 37卷

关键词：

process/model mismatch; PCA; batch processes; latent variable models;

D O I：

暂无

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

Process/model mismatch may arise when a first-principles model is challenged against historical experimental data. In this study, a methodology recently proposed to diagnose the root cause of the mismatch in continuous processes is extended to batch systems, taking a batch drying process as a case study to test the proposed methodology. The likely sources of the mismatch are identified using a multivariate statistical model and analyzing the model residuals as well as the scores shifts. Two simulated examples demonstrate the effectiveness of the proposed methodology.

引用

页码：437 / 442

页数：6

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