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Nonlinear fault detection and diagnosis using Kernel based techniques applied to a pilot distillation colomn
Dissertation (MEng (Control Engineering))--University of Pretoria, 2008.
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| Format: | Thesis |
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University of Pretoria
2013
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| _version_ | 1867613463243653121 |
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| access_status_str | Open Access |
| author2 | De Vaal, Philip L. |
| author_browse | De Vaal, Philip L. |
| author_facet | De Vaal, Philip L. |
| collection | Thesis |
| dc_rights_str_mv | © University of Pretor |
| description | Dissertation (MEng (Control Engineering))--University of Pretoria, 2008. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/23256 |
| institution | University of Pretoria (South Africa) |
| last_indexed | 2026-06-10T12:36:32.683Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2013 |
| publishDateRange | 2013 |
| publishDateSort | 2013 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/23256 Nonlinear fault detection and diagnosis using Kernel based techniques applied to a pilot distillation colomn De Vaal, Philip L. davidph@mintek.co.za Phillpotts, David Nicholas Charles Statistical process control Fault diagnosis Fault detection Kernel based methods UCTD Dissertation (MEng (Control Engineering))--University of Pretoria, 2008. Fault detection and diagnosis is an important problem in process engineering. In this dissertation, use of multivariate techniques for fault detection and diagnosis is explored in the context of statistical process control. Principal component analysis and its extension, kernel principal component analysis, are proposed to extract features from process data. Kernel based methods have the ability to model nonlinear processes by forming higher dimensional representations of the data. Discriminant methods can be used to extend on feature extraction methods by increasing the isolation between different faults. This is shown to aid fault diagnosis. Linear and kernel discriminant analysis are proposed as fault diagnosis methods. Data from a pilot scale distillation column were used to explore the performance of the techniques. The models were trained with normal and faulty operating data. The models were tested with unseen and/or novel fault data. All the techniques demonstrated at least some fault detection and diagnosis ability. Linear PCA was particularly successful. This was mainly due to the ease of the training and the ability to relate the scores back to the input data. The attributes of these multivariate statistical techniques were compared to the goals of statistical process control and the desirable attributes of fault detection and diagnosis systems. Chemical Engineering MEng Unrestricted 2013-09-06T14:49:36Z 2008-05-19 2013-09-06T14:49:36Z 2007-09-05 2008-05-19 2008-01-15 Dissertation Phillpotts, DNC 2008, Nonlinear fault detection and diagnosis using Kernel based techniques applied to a pilot distillation colomn, MEng Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/23256> http://hdl.handle.net/2263/23256 http://upetd.up.ac.za/thesis/available/etd-01152008-125258/ © University of Pretor application/pdf University of Pretoria |
| spellingShingle | Statistical process control Fault diagnosis Fault detection Kernel based methods UCTD Nonlinear fault detection and diagnosis using Kernel based techniques applied to a pilot distillation colomn |
| title | Nonlinear fault detection and diagnosis using Kernel based techniques applied to a pilot distillation colomn |
| title_full | Nonlinear fault detection and diagnosis using Kernel based techniques applied to a pilot distillation colomn |
| title_fullStr | Nonlinear fault detection and diagnosis using Kernel based techniques applied to a pilot distillation colomn |
| title_full_unstemmed | Nonlinear fault detection and diagnosis using Kernel based techniques applied to a pilot distillation colomn |
| title_short | Nonlinear fault detection and diagnosis using Kernel based techniques applied to a pilot distillation colomn |
| title_sort | nonlinear fault detection and diagnosis using kernel based techniques applied to a pilot distillation colomn |
| topic | Statistical process control Fault diagnosis Fault detection Kernel based methods UCTD |
| url | http://hdl.handle.net/2263/23256 http://upetd.up.ac.za/thesis/available/etd-01152008-125258/ |