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The application of advanced signal processing techniques to the condition monitoring of electrical machine drive systems
Includes bibliographical references (leaves 128-129).
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Electrical Engineering
2014
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| _version_ | 1867613477869191168 |
|---|---|
| access_status_str | Open Access |
| author | Barendse, Paul Stanley |
| author2 | Pillay, Pragasen |
| author_browse | Barendse, Paul Stanley Pillay, Pragasen |
| author_facet | Pillay, Pragasen Barendse, Paul Stanley |
| author_sort | Barendse, Paul Stanley |
| collection | Thesis |
| description | Includes bibliographical references (leaves 128-129). |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/7460 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:36:46.818Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| 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:11427/7460 The application of advanced signal processing techniques to the condition monitoring of electrical machine drive systems Barendse, Paul Stanley Pillay, Pragasen Electrical Engineering Includes bibliographical references (leaves 128-129). The thesis examines the use of two time-frequency domain signal processing tools in its application to condition monitoring of electrical machine drive systems. The mathematical and signal processing tools which are explored are wavelet analysis and a non-stationary adaptive signal processing algorithm. Four specific applications are identified for the research. These applications were specifically chosen to encapsulate important issues in condition monitoring of variable speed drive systems. The main aim of the project is to highlight the need for fault detection during machine transients and to illustrate the effectiveness of incorporating and adapting these new class of algorithms to detect faults in electrical machine drive systems during non-stationary conditions. 2014-09-15T07:24:44Z 2014-09-15T07:24:44Z 2007 Doctoral Thesis Doctoral PhD http://hdl.handle.net/11427/7460 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Electrical Engineering Barendse, Paul Stanley The application of advanced signal processing techniques to the condition monitoring of electrical machine drive systems |
| thesis_degree_str | Doctoral |
| title | The application of advanced signal processing techniques to the condition monitoring of electrical machine drive systems |
| title_full | The application of advanced signal processing techniques to the condition monitoring of electrical machine drive systems |
| title_fullStr | The application of advanced signal processing techniques to the condition monitoring of electrical machine drive systems |
| title_full_unstemmed | The application of advanced signal processing techniques to the condition monitoring of electrical machine drive systems |
| title_short | The application of advanced signal processing techniques to the condition monitoring of electrical machine drive systems |
| title_sort | application of advanced signal processing techniques to the condition monitoring of electrical machine drive systems |
| topic | Electrical Engineering |
| url | http://hdl.handle.net/11427/7460 |
| work_keys_str_mv | AT barendsepaulstanley theapplicationofadvancedsignalprocessingtechniquestotheconditionmonitoringofelectricalmachinedrivesystems AT barendsepaulstanley applicationofadvancedsignalprocessingtechniquestotheconditionmonitoringofelectricalmachinedrivesystems |