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Development of a wind turbine condition monitoring facility for drivetrain torsional dynamics investigations
Dissertation (MEng)--University of Pretoria, 2018.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2018
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| _version_ | 1867613506520481792 |
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| access_status_str | Open Access |
| author2 | Heyns, P.S. (Philippus Stephanus) |
| author_browse | Heyns, P.S. (Philippus Stephanus) |
| author_facet | Heyns, P.S. (Philippus Stephanus) |
| collection | Thesis |
| dc_rights_str_mv | © 2018 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MEng)--University of Pretoria, 2018. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/66388 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:37:14.131Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| 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:2263/66388 Development of a wind turbine condition monitoring facility for drivetrain torsional dynamics investigations Heyns, P.S. (Philippus Stephanus) Van Niekerk, Paul UCTD Wind turbine condition monitoring Drivetrain torsional dynamics Wind energy Engineering, built environment and information technology theses SDG-07 SDG-07: Affordable and clean energy Engineering, built environment and information technology theses SDG-09 SDG-09: Industry, innovation and infrastructure Engineering, built environment and information technology theses SDG-12 SDG-12: Responsible consumption and production Dissertation (MEng)--University of Pretoria, 2018. Maintenance can be performed according to one of two strategies, failure based or condition based. In most cases, where large and expensive assets such as wind turbines are operated on a continuous basis, condition based maintenance is preferred. However, condition based maintenance relies on the continuous and accurate gathering of condition-information of the particular machine and its various components. This dissertation reports the experimental and numerical work performed as part of the development of an experimental facility that will allow the development of condition monitoring techniques for wind turbines. This work is focussed on the torsional dynamics of a wind turbine setup. A physical setup, consisting of a 1.6 m diameter turbine, a 1:1. ̇ speed-multiplication gearbox, and a 24 Volt direct current generator is built. All of it is mounted within an open-return wind tunnel, which is also designed and built as part of this work. The following two cost-effective experimental techniques are used to measure the torsional natural frequencies: a shaft encoder tachometer from which instantaneous rotational frequency is obtained, and power signal analysis, where the generated voltage is recorded and analysed. It is shown how an algorithm developed by Diamond et al. (2016) is used for the shaft encoder geometry compensation. Frequency spectra based on Fourier transforms and short time Fourier transforms are used to identify harmonic frequencies. Both measurement techniques proves useful to identify not only natural frequencies of torsional vibration, but also various characteristic frequencies of the drivetrain such as shaft rotation, blade pass, gear mesh and generator armature. It is found that power signal analysis is more useful to identify the characteristic frequencies. Torsional dynamics of the drivetrain and its components are also investigated with the following two numerical methods: an eight-degree-of-freedom torsional Lumped Mass Model (LMM), and a three-dimensional Finite Element Model (FEM). Torsional mode shapes and frequencies are calculated with both methods and a good agreement is found in the lower four modes. Numerical results are then compared with the experimental results, where there is also good agreement in the lower four modes. Model updating is performed on the FEM and by changing the torsional stiffness of the flexible couplings, the difference between measured and calculated natural frequencies are reduced to less than 6 %. It is concluded that future models should address lateral vibration of the drivetrain and the support structure. From this study the following is contributed to the wind turbine condition monitoring field: considerations for the design and a working example of an experimental facility for investigating torsional dynamics, illustration of two measurement techniques, and two types of validated numerical models. mi2025 Mechanical and Aeronautical Engineering MEng Unrestricted SDG-07: Affordable and clean energy SDG-09: Industry, innovation and infrastructure SDG-12: Responsible consumption and production 2018-08-30T09:03:48Z 2018-08-30T09:03:48Z 2018 2018 Dissertation Van Niekerk, P 2018, Development of a wind turbine condition monitoring facility for drivetrain torsional dynamics investigations, MEng Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/66388> A2018 http://hdl.handle.net/2263/66388 en © 2018 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Wind turbine condition monitoring Drivetrain torsional dynamics Wind energy Engineering, built environment and information technology theses SDG-07 SDG-07: Affordable and clean energy Engineering, built environment and information technology theses SDG-09 SDG-09: Industry, innovation and infrastructure Engineering, built environment and information technology theses SDG-12 SDG-12: Responsible consumption and production Development of a wind turbine condition monitoring facility for drivetrain torsional dynamics investigations |
| title | Development of a wind turbine condition monitoring facility for drivetrain torsional dynamics investigations |
| title_full | Development of a wind turbine condition monitoring facility for drivetrain torsional dynamics investigations |
| title_fullStr | Development of a wind turbine condition monitoring facility for drivetrain torsional dynamics investigations |
| title_full_unstemmed | Development of a wind turbine condition monitoring facility for drivetrain torsional dynamics investigations |
| title_short | Development of a wind turbine condition monitoring facility for drivetrain torsional dynamics investigations |
| title_sort | development of a wind turbine condition monitoring facility for drivetrain torsional dynamics investigations |
| topic | UCTD Wind turbine condition monitoring Drivetrain torsional dynamics Wind energy Engineering, built environment and information technology theses SDG-07 SDG-07: Affordable and clean energy Engineering, built environment and information technology theses SDG-09 SDG-09: Industry, innovation and infrastructure Engineering, built environment and information technology theses SDG-12 SDG-12: Responsible consumption and production |
| url | http://hdl.handle.net/2263/66388 |