Monitoring of continuous crystallization process

Author

Aparna, A.M. ; Kundu, Madhusree

Author_Institution

Dept. of Chem. Eng., N.I.T. Rourkela, Rourkela, India

fYear

2014

fDate

10-11 July 2014

Firstpage

1146

Lastpage

1149

Abstract

Monitoring and control of continuous crystallization processes are highly challenging due to their nonlinear, multivariate and highly correlated nature. Present paper furnishes the successful implementation of various chemometric techniques like clustering of time series data and moving window based pattern matching aiming towards fault detection and classification of different operating conditions of a continuous crystallizer. PCA based combined similarity was chosen as the index of clustering as well as pattern matching.

Keywords

chemical engineering; crystallisation; fault diagnosis; multivariable control systems; nonlinear control systems; pattern matching; principal component analysis; process control; process monitoring; time series; PCA based combined similarity; chemometric techniques; continuous crystallization process monitoring; continuous crystallization processes control; continuous crystallizer; fault classification; fault detection; moving window based pattern matching; time series data clustering; Crystallization; Crystallizers; Databases; Mathematical model; Monitoring; Pattern matching; Principal component analysis; PCA similarity; chemometrics; clustering; continuous; crystallizer;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2014 International Conference on

Conference_Location

Kanyakumari

Print_ISBN

978-1-4799-4191-9

Type

conf

DOI

10.1109/ICCICCT.2014.6993134

Filename

6993134