Enhancement of PCA-based fault detection system through utilising dissimilarity matrix for continuous-based process

This research is about enhancement of PCA-based fault detection system through utilizing dissimilarity matrix. Nowadays, the chemical process industry is highly based on the non-linear relationships between measured variables. However, the conventional PCA-based MSPC is no longer effective because i...

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Main Author:	Nur Afifah, Hassan
Format:	Undergraduates Project Papers
Language:	English
Published:	2013
Subjects:	QA Mathematics
Online Access:	http://umpir.ump.edu.my/id/eprint/7160/ http://umpir.ump.edu.my/id/eprint/7160/ http://umpir.ump.edu.my/id/eprint/7160/1/Enhancement_of_PCA-based_fault_detection_system_through_utilising_dissimilarity_matrix.pdf

id	ump-7160
recordtype	eprints
spelling	ump-71602015-03-03T09:34:34Z http://umpir.ump.edu.my/id/eprint/7160/ Enhancement of PCA-based fault detection system through utilising dissimilarity matrix for continuous-based process Nur Afifah, Hassan QA Mathematics This research is about enhancement of PCA-based fault detection system through utilizing dissimilarity matrix. Nowadays, the chemical process industry is highly based on the non-linear relationships between measured variables. However, the conventional PCA-based MSPC is no longer effective because it only valid for the linear relationships between measured variables. Due in order to solve this problem, the technique of dissimilarity matrix is used in multivariate statistical process control as alternative technique which models the non-linear process and can improve the process monitoring performance. The conventional PCA system was run and the dissimilarity system was developed and lastly the monitoring performance in each technique were compared and analysed to achieve aims of this research. This research is to be done by using Matlab software. The findings of this study are illustrated in the form of Hotelling’s T2 and Squared Prediction Errors (SPE) monitoring statistics to be analysed. As a conclusion, the dissimilarity system is comparable to the conventional method. Thus can be the other alternative ways in the process monitoring performance. Finally, it is recommended to use data from other chemical processing systems for more concrete justification of the new technique. 2013 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/7160/1/Enhancement_of_PCA-based_fault_detection_system_through_utilising_dissimilarity_matrix.pdf Nur Afifah, Hassan (2013) Enhancement of PCA-based fault detection system through utilising dissimilarity matrix for continuous-based process. Faculty of Chemical & Natural Resources Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:75732&theme=UMP2
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA Mathematics
spellingShingle	QA Mathematics Nur Afifah, Hassan Enhancement of PCA-based fault detection system through utilising dissimilarity matrix for continuous-based process
description	This research is about enhancement of PCA-based fault detection system through utilizing dissimilarity matrix. Nowadays, the chemical process industry is highly based on the non-linear relationships between measured variables. However, the conventional PCA-based MSPC is no longer effective because it only valid for the linear relationships between measured variables. Due in order to solve this problem, the technique of dissimilarity matrix is used in multivariate statistical process control as alternative technique which models the non-linear process and can improve the process monitoring performance. The conventional PCA system was run and the dissimilarity system was developed and lastly the monitoring performance in each technique were compared and analysed to achieve aims of this research. This research is to be done by using Matlab software. The findings of this study are illustrated in the form of Hotelling’s T2 and Squared Prediction Errors (SPE) monitoring statistics to be analysed. As a conclusion, the dissimilarity system is comparable to the conventional method. Thus can be the other alternative ways in the process monitoring performance. Finally, it is recommended to use data from other chemical processing systems for more concrete justification of the new technique.
format	Undergraduates Project Papers
author	Nur Afifah, Hassan
author_facet	Nur Afifah, Hassan
author_sort	Nur Afifah, Hassan
title	Enhancement of PCA-based fault detection system through utilising dissimilarity matrix for continuous-based process
title_short	Enhancement of PCA-based fault detection system through utilising dissimilarity matrix for continuous-based process
title_full	Enhancement of PCA-based fault detection system through utilising dissimilarity matrix for continuous-based process
title_fullStr	Enhancement of PCA-based fault detection system through utilising dissimilarity matrix for continuous-based process
title_full_unstemmed	Enhancement of PCA-based fault detection system through utilising dissimilarity matrix for continuous-based process
title_sort	enhancement of pca-based fault detection system through utilising dissimilarity matrix for continuous-based process
publishDate	2013
url	http://umpir.ump.edu.my/id/eprint/7160/ http://umpir.ump.edu.my/id/eprint/7160/ http://umpir.ump.edu.my/id/eprint/7160/1/Enhancement_of_PCA-based_fault_detection_system_through_utilising_dissimilarity_matrix.pdf
first_indexed	2023-09-18T22:03:35Z
last_indexed	2023-09-18T22:03:35Z
_version_	1777414560476561408

Enhancement of PCA-based fault detection system through utilising dissimilarity matrix for continuous-based process

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