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Fault Detection and Diagnosis via Improved Statistical Process Control: Chemical Process Application - Couverture souple

Harun, Noorlisa; Ibrahim, Kamarul Asri

 
9783659177651: Fault Detection and Diagnosis via Improved Statistical Process Control: Chemical Process Application
Couverture souple
ISBN 10 : 3659177652 ISBN 13 : 9783659177651
Editeur : LAP LAMBERT Academic Publishing, 2012

Synopsis

Multivariate Statistical Process Control (MSPC) technique has been widely used for fault detection and diagnosis (FDD). Currently, contribution plots are used as basic tools for fault diagnosis in MSPC approaches. This plot does not exactly diagnose the fault, it just provides greater insight into possible causes and thereby narrow down the search. Hence, the cause of the faults cannot be found in a straightforward manner. Therefore, this study is conducted to introduce a new approach for detecting and diagnosing fault via correlation technique. Multivariate analysis technique i.e Principal Component Analysis, PCA and Partial Correlation Analysis, PCorrA are utilized to determine the correlation coefficient between quality variables and process variables. A precut multicomponent distillation column that has been installed with controllers is used as the study unit operation. Improved SPC method is implemented to detect and diagnose various kinds of faults, which occur in the process. Individual charting technique such as Shewhart, Exponential Weight Moving Average (EWMA) and Moving Average and Moving Range (MAMR) charts are used to facilitate the FDD.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Multivariate Statistical Process Control (MSPC) technique has been widely used for fault detection and diagnosis (FDD). Currently, contribution plots are used as basic tools for fault diagnosis in MSPC approaches. This plot does not exactly diagnose the fault, it just provides greater insight into possible causes and thereby narrow down the search. Hence, the cause of the faults cannot be found in a straightforward manner. Therefore, this study is conducted to introduce a new approach for detecting and diagnosing fault via correlation technique. Multivariate analysis technique i.e Principal Component Analysis, PCA and Partial Correlation Analysis, PCorrA are utilized to determine the correlation coefficient between quality variables and process variables. A precut multicomponent distillation column that has been installed with controllers is used as the study unit operation. Improved SPC method is implemented to detect and diagnose various kinds of faults, which occur in the process. Individual charting technique such as Shewhart, Exponential Weight Moving Average (EWMA) and Moving Average and Moving Range (MAMR) charts are used to facilitate the FDD.

Biographie de l'auteur

Noorlisa Harun received her B.Eng. (Chem.) and M.Sc. (Chem.) from Universiti Teknologi Malaysia (UTM), and PhD in chemical engineering from University of Waterloo, Canada.  Currently, Noorlisa is a senior lecturer at Universiti Malaysia Pahang and a member of Process Systems Engineering Group (PSEG).

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2012
Langue
anglais
ISBN 10 
3659177652
ISBN 13 
9783659177651
Reliure
Broché
Nombre de pages
172
Coordonnées du fabricant
non disponible
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