Modal-based damage identification for the nonlinear model of modern wind turbine blade
Mohammad M. Rezaei,
Mehdi Behzad,
Hamed Moradi and
Hassan Haddadpour
Renewable Energy, 2016, vol. 94, issue C, 391-409
Abstract:
In this paper, the modal-based indices are used in damage identification of the wind turbine blade. In contrast of many of previous researches, the geometric nonlinearity due to the large structural deformation of the modern wind turbines blade is considered. In the first step, the finite element model (FEM) of the rotating blade is solved to obtain the modal features of the deformed structure under operational aerodynamic loading. Next, the accuracy and efficiency of the various modal-based damage indices including the frequency, mode shape, curvature of mode shape, modal assurance, modal strain energy (MSE) and the difference of indices (between the intact and damaged blades) are investigated. To adapt the MSE index calculation in nonlinear modeling, a new approach is introduced to include the effects of the structural nonlinearity. Furthermore, the effect of the damage length, its location and severity and also the effect of rotational speed and amplitude of loading are studied. The generic 5-MW NREL blade is used for the simulation study. The results show enough sensitivity of the mode shape curvature and MSE indices to the local damages. Moreover, the importance of geometric nonlinearity in the damage detection of the modern wind turbines is demonstrated.
Keywords: Modal-based indices; Damage identification; Wind turbine blade; Geometric nonlinearity; Modal strain energy; Operational loading (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148116302580
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:94:y:2016:i:c:p:391-409
DOI: 10.1016/j.renene.2016.03.074
Access Statistics for this article
Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides
More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().