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Multivariate Process Monitoring Of Structural Changes in A CSTR System

Process monitoring traditionally using univariate process monitoring approach where each of individual variables is monitored separately. In this approach process variables interaction is difficult to be monitored and therefore multivariable statistical process monitoring (MSPM) was introduced to ca...

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Main Author: Ishak, Mohd Hanif
Format: Final Year Project
Language:English
Published: Universiti Teknologi PETRONAS 2013
Subjects:
TP Chemical technology
Online Access:http://utpedia.utp.edu.my/8398/1/%5BFYP%20Dissertation%5D-Multivariate%20Process%20Monitoring%20of%20Structural%20Changes_Mohd%20Hanif%20Ishak_12018.pdf
http://utpedia.utp.edu.my/8398/
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spelling my-utp-utpedia.83982013-10-09T11:07:23Z http://utpedia.utp.edu.my/8398/ Multivariate Process Monitoring Of Structural Changes in A CSTR System Ishak, Mohd Hanif TP Chemical technology Process monitoring traditionally using univariate process monitoring approach where each of individual variables is monitored separately. In this approach process variables interaction is difficult to be monitored and therefore multivariable statistical process monitoring (MSPM) was introduced to cater the drawback of univariate process monitoring. MSPM has a major advantage in detecting change in variables relationship or also known as structural changes. Despite of the advantage, most of studies are focusing on change in variables rather than the variables interaction. In this study, PCA based detection techniques performance including PCA, dynamic PCA and nonlinear PCA has been evaluated under change in reaction kinetic and change in heat transfer coefficient. Hotelling T2 and SPE chart are employed as the fault detection techniques. The project mainly focusing on fault detectability and fault detection time. All the PCA based approaches are able to detect the structural changes. Nonlinear PCA shows the fastest detectability followed by dynamic PCA and PCA. For highly nonlinear system, Nonlinear PCA are able to detects the fault the fast but the nonlinear PCA not performing the best when encounter with lesser degree of nonlinear data set. Universiti Teknologi PETRONAS 2013-05 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/8398/1/%5BFYP%20Dissertation%5D-Multivariate%20Process%20Monitoring%20of%20Structural%20Changes_Mohd%20Hanif%20Ishak_12018.pdf Ishak, Mohd Hanif (2013) Multivariate Process Monitoring Of Structural Changes in A CSTR System. Universiti Teknologi PETRONAS. (Unpublished)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic TP Chemical technology
spellingShingle TP Chemical technology
Ishak, Mohd Hanif
Multivariate Process Monitoring Of Structural Changes in A CSTR System
description Process monitoring traditionally using univariate process monitoring approach where each of individual variables is monitored separately. In this approach process variables interaction is difficult to be monitored and therefore multivariable statistical process monitoring (MSPM) was introduced to cater the drawback of univariate process monitoring. MSPM has a major advantage in detecting change in variables relationship or also known as structural changes. Despite of the advantage, most of studies are focusing on change in variables rather than the variables interaction. In this study, PCA based detection techniques performance including PCA, dynamic PCA and nonlinear PCA has been evaluated under change in reaction kinetic and change in heat transfer coefficient. Hotelling T2 and SPE chart are employed as the fault detection techniques. The project mainly focusing on fault detectability and fault detection time. All the PCA based approaches are able to detect the structural changes. Nonlinear PCA shows the fastest detectability followed by dynamic PCA and PCA. For highly nonlinear system, Nonlinear PCA are able to detects the fault the fast but the nonlinear PCA not performing the best when encounter with lesser degree of nonlinear data set.
format Final Year Project
author Ishak, Mohd Hanif
author_facet Ishak, Mohd Hanif
author_sort Ishak, Mohd Hanif
title Multivariate Process Monitoring Of Structural Changes in A CSTR System
title_short Multivariate Process Monitoring Of Structural Changes in A CSTR System
title_full Multivariate Process Monitoring Of Structural Changes in A CSTR System
title_fullStr Multivariate Process Monitoring Of Structural Changes in A CSTR System
title_full_unstemmed Multivariate Process Monitoring Of Structural Changes in A CSTR System
title_sort multivariate process monitoring of structural changes in a cstr system
publisher Universiti Teknologi PETRONAS
publishDate 2013
url http://utpedia.utp.edu.my/8398/1/%5BFYP%20Dissertation%5D-Multivariate%20Process%20Monitoring%20of%20Structural%20Changes_Mohd%20Hanif%20Ishak_12018.pdf
http://utpedia.utp.edu.my/8398/
_version_ 1739831569702453248
score 13.211869

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