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Lookup NU author(s): Dr Wenxian YangORCiD
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Accessing difficulties and harsh environments require more advanced condition monitoring techniques to ensure the high availability of offshore wind turbines. Empirical mode decomposition (EMD) has been shown to be a promising technique for meeting this need. However, EMD was developed for one-dimensional signals, unable to carry out an information fusion function which is of importance to reach a reliable condition monitoring conclusion. Therefore, bivariate empirical mode decomposition (BEMD) is investigated in this paper to assess whether it could be a better solution for wind turbine condition monitoring. The effectiveness of the proposed technique in detecting machine incipient fault is compared with EMD and a recently developed wavelet-based ‘energy tracking’ technique. Experiments have shown that the proposed BEMD-based technique is more convenient than EMD for processing shaft vibration signals, and more powerful than EMD and wavelet-based techniques in terms of processing the non-stationary and nonlinear wind turbine condition monitoring signals and detecting incipient mechanical and electrical faults.
Author(s): Yang W, Court R, Tavner P, Crabtree C
Publication type: Article
Publication status: Published
Journal: Journal of Sound and Vibration
Year: 2011
Volume: 330
Issue: 15
Pages: 3766-3782
Print publication date: 18/07/2011
ISSN (print): 0022-460X
ISSN (electronic): 1095-8568
Publisher: Elsevier Ltd.
URL: http://dx.doi.org/10.1016/j.jsv.2011.02.027
DOI: 10.1016/j.jsv.2011.02.027
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