dc.contributor.author | Shanbr, Suliman | |
dc.contributor.author | Elasha, Faris | |
dc.contributor.author | Elforjani, Mohamed | |
dc.contributor.author | Teixeira, Joao | |
dc.date.accessioned | 2018-04-30T18:05:51Z | |
dc.date.available | 2018-04-30T18:05:51Z | |
dc.date.issued | 2018-04-01 | |
dc.identifier.citation | Shanbr , S , Elasha , F , Elforjani , M & Teixeira , J 2018 , ' Detection of natural crack in wind turbine gearbox ' , Renewable Energy , vol. 118 , pp. 172-179 . https://doi.org/10.1016/j.renene.2017.10.104 | |
dc.identifier.issn | 0960-1481 | |
dc.identifier.uri | http://hdl.handle.net/2299/20000 | |
dc.description | This document is the Accepted Manuscript version of the following article: Suliman Shanbr, Faris Elasha, Mohamed Elforjani, and Joao Teixeira, ‘Detection of natural crack in wind turbine gearbox’, Renewable Energy, vol. 118: 172-179, October 2017. Under embargo. Embargo end date: 30 October 2018. The final, published version is available online at doi: https://doi.org/10.1016/j.renene.2017.10.104. © 2017 Elsevier Ltd. This manuscript version is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. | |
dc.description.abstract | One of the most challenging scenarios in bearing diagnosis is the extraction of fault signatures from within other strong components which mask the vibration signal. Usually, the bearing vibration signals are dominated by those of other components such as gears and shafts. A good example of this scenario is the wind turbine gearbox which presents one of the most difficult bearing detection tasks. The non-stationary signal analysis is considered one of the main topics in the field of machinery fault diagnosis. In this paper, a set of signal processing techniques has been studied to investigate their feasibility for bearing fault detection in wind turbine gearbox. These techniques include statistical condition indicators, spectral kurtosis, and envelope analysis. The results of vibration analysis showed the possibility of bearing fault detection in wind turbine high-speed shafts using multiple signal processing techniques. However, among these signal processing techniques, spectral kurtosis followed by envelope analysis provides early fault detection compared to the other techniques employed. In addition, outer race bearing fault indicator provides clear indication of the crack severity and progress. | en |
dc.format.extent | 8 | |
dc.format.extent | 1052144 | |
dc.language.iso | eng | |
dc.relation.ispartof | Renewable Energy | |
dc.subject | Condition monitoring | |
dc.subject | Natural cracks | |
dc.subject | Rotating machinery | |
dc.subject | Signal processing | |
dc.subject | Vibration | |
dc.subject | Renewable Energy, Sustainability and the Environment | |
dc.title | Detection of natural crack in wind turbine gearbox | en |
dc.contributor.institution | School of Engineering and Technology | |
dc.contributor.institution | Centre for Engineering Research | |
dc.description.status | Peer reviewed | |
dc.date.embargoedUntil | 2018-10-30 | |
dc.identifier.url | http://www.scopus.com/inward/record.url?scp=85034054496&partnerID=8YFLogxK | |
rioxxterms.versionofrecord | 10.1016/j.renene.2017.10.104 | |
rioxxterms.type | Journal Article/Review | |
herts.preservation.rarelyaccessed | true | |