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Adaptive noise cancelling applied to machine condition monitoring
Includes bibliography.
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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_ | 1867614150898745344 |
|---|---|
| access_status_str | Open Access |
| author | Bremer, Paul Graham |
| author2 | Jongens, A W D |
| author_browse | Bremer, Paul Graham Jongens, A W D |
| author_facet | Jongens, A W D Bremer, Paul Graham |
| author_sort | Bremer, Paul Graham |
| collection | Thesis |
| description | Includes bibliography. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/8349 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:47:28.669Z |
| 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:11427/8349 Adaptive noise cancelling applied to machine condition monitoring Bremer, Paul Graham Jongens, A W D Electrical and Electronic Engineering Includes bibliography. The objective of this thesis is to determine whether Adaptive Noise Cancelling can be used successfully in determining the state of machine elements. In addition, this thesis was used to gain experience in real-time computing. This was done by designing and building a real-time machine monitoring package using an IBM PC and a TMS 320C25 digital signal-processing chip manufactured by Texas Instruments. To determine which adaptive algorithm should be used in the package, experiments were carried out on a computer with different types of adaptive noise cancelling algorithms, the two main ones being the Least-Mean-Squares (LMS) and Recursive-Least-Squares (RLS) algorithms. 2014-10-11T12:06:11Z 2014-10-11T12:06:11Z 1990 Master Thesis Masters MSc http://hdl.handle.net/11427/8349 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Electrical and Electronic Engineering Bremer, Paul Graham Adaptive noise cancelling applied to machine condition monitoring |
| thesis_degree_str | Master's |
| title | Adaptive noise cancelling applied to machine condition monitoring |
| title_full | Adaptive noise cancelling applied to machine condition monitoring |
| title_fullStr | Adaptive noise cancelling applied to machine condition monitoring |
| title_full_unstemmed | Adaptive noise cancelling applied to machine condition monitoring |
| title_short | Adaptive noise cancelling applied to machine condition monitoring |
| title_sort | adaptive noise cancelling applied to machine condition monitoring |
| topic | Electrical and Electronic Engineering |
| url | http://hdl.handle.net/11427/8349 |
| work_keys_str_mv | AT bremerpaulgraham adaptivenoisecancellingappliedtomachineconditionmonitoring |