Prediction of wind turbine generator bearing failure through analysis of high‐frequency vibration data and the application of support vector machine algorithms-Reference-Cited by-同舟云学术

Prediction of wind turbine generator bearing failure through analysis of high‐frequency vibration data and the application of support vector machine algorithms

Published:2019-06-18 Issue:18 Volume:2019 Page:4965-4969
ISSN:2051-3305
Container-title:The Journal of Engineering
language:en
Short-container-title:J. eng.

Author:

Turnbull Alan¹,Carroll James¹,Koukoura Sofia¹,McDonald Alasdair¹

Affiliation:

1. Electrical and Electronic Engineering, University of StrathclydeGlasgowUK

Funder

Engineering and Physical Sciences Research Council

Publisher

Institution of Engineering and Technology (IET)

Subject

General Engineering,Energy Engineering and Power Technology,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/joe.2018.9281

Reference8 articles.

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2. Reliability of wind turbine subassemblies;Spinato F.;IET Renew. Power Gener.,2009

3. CarrollJ. McDonaldA. McMillanD.: ‘Reliability study of wind turbines with DFIG and PMG drivetrains’

4. WilkinsonM. HarmanK. SpinatoF.et al.: ‘Measuring wind turbine reliability – results of the reliawind project’ Proc. Eur. Wind Energy Conf. Brussels Belgium 14–17 March 2011

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