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The importance of selecting the optimal number of principal components for fault detection using principal component analysis
Includes summary.
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Electrical Engineering
2015
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| _version_ | 1867613257272918016 |
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| access_status_str | Open Access |
| author | Khwambala, Patricia Helen |
| author2 | Braae, Martin |
| author_browse | Braae, Martin Khwambala, Patricia Helen |
| author_facet | Braae, Martin Khwambala, Patricia Helen |
| author_sort | Khwambala, Patricia Helen |
| collection | Thesis |
| description | Includes summary. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/11930 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:33:15.376Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/11930 The importance of selecting the optimal number of principal components for fault detection using principal component analysis Khwambala, Patricia Helen Braae, Martin Electrical Engineering Includes summary. Includes bibliographical references. Fault detection and isolation are the two fundamental building blocks of process monitoring. Accurate and efficient process monitoring increases plant availability and utilization. Principal component analysis is one of the statistical techniques that are used for fault detection. Determination of the number of PCs to be retained plays a big role in detecting a fault using the PCA technique. In this dissertation focus has been drawn on the methods of determining the number of PCs to be retained for accurate and effective fault detection in a laboratory thermal system. SNR method of determining number of PCs, which is a relatively recent method, has been compared to two commonly used methods for the same, the CPV and the scree test methods. 2015-01-10T13:21:29Z 2015-01-10T13:21:29Z 2012 Master Thesis Masters MSc http://hdl.handle.net/11427/11930 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Electrical Engineering Khwambala, Patricia Helen The importance of selecting the optimal number of principal components for fault detection using principal component analysis |
| thesis_degree_str | Master's |
| title | The importance of selecting the optimal number of principal components for fault detection using principal component analysis |
| title_full | The importance of selecting the optimal number of principal components for fault detection using principal component analysis |
| title_fullStr | The importance of selecting the optimal number of principal components for fault detection using principal component analysis |
| title_full_unstemmed | The importance of selecting the optimal number of principal components for fault detection using principal component analysis |
| title_short | The importance of selecting the optimal number of principal components for fault detection using principal component analysis |
| title_sort | importance of selecting the optimal number of principal components for fault detection using principal component analysis |
| topic | Electrical Engineering |
| url | http://hdl.handle.net/11427/11930 |
| work_keys_str_mv | AT khwambalapatriciahelen theimportanceofselectingtheoptimalnumberofprincipalcomponentsforfaultdetectionusingprincipalcomponentanalysis AT khwambalapatriciahelen importanceofselectingtheoptimalnumberofprincipalcomponentsforfaultdetectionusingprincipalcomponentanalysis |