DocumentCode :
2308600
Title :
Detection and Damage Diagnosis for Wind Turbine Blades Based on the Theory of Length Fractal Dimension on Dynamic Properties
Author :
Yuanying Mei ; Yuxiu Xu ; Zhiqiang Wang
Author_Institution :
Sch. of Mech. & Electr. Eng., Tianjin Polytech. Univ., Tianjin, China
Volume :
1
fYear :
2010
fDate :
13-14 March 2010
Firstpage :
1089
Lastpage :
1092
Abstract :
Blades are the key components of large scale wind turbine. It is significant to do the detection and damage diagnosis for it. However, the changing circumstance and variable load always make the blade´s vibration signal complex. To detect damage information of blade, some dyn parameters are picked up from the signal measured and used as the characteristic. In this paper, a dynamics model of 300w wind turbine has been build in FEM. Via modal analysis and dynamics emulate, obtain dyn properties, get the characteristic frequency, vibration shape and response data. Apply the theory of length fractal dimension on nonlinear vibration system to calculate the length fractal dimension in the blade´s normal or damaged situation. The dimension can be used as the surveying characteristic to do the diagnosis. The method presented in this paper provides an academic reference and an example to research the detection and damage diagnosis further for large scale wind turbine blades.
Keywords :
blades; finite element analysis; inspection; vibrations; wind turbines; FEM; damage detection; damage diagnosis; finite element method; length fractal dimension; modal analysis; vibration; wind turbine blades; Aerodynamics; Blades; Fractals; Large-scale systems; Length measurement; Mechatronics; Modal analysis; Nonlinear dynamical systems; Vibrations; Wind turbines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location :
Changsha City
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
Type :
conf
DOI :
10.1109/ICMTMA.2010.758
Filename :
5460334
Link To Document :
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