Title :
Operational Fault Feature Extraction of Blade Based on Vibration of Wind Turbine
Author :
Yan Jun ; Xu Yuxiu
Author_Institution :
Sch. of Mech. & Electr. Eng., Tianjin Polytech. Univ., Tianjin, China
Abstract :
By analyzing the acquisition data of the wind turbine, we calculate the correlation dimension of the vibration signals, and take it as the feature parameter which typifies the working state of blades. The calculation results indicated that the correlation dimension is effective to reflect the dynamic structure of chaotic attractor. Thus the correlation dimension of blades´ vibration signals can be used to classify the different working state of blades effectively. Experiments have also shown that this method is especially effective at working state monitoring and at fault diagnosis, and can achieve higher precision in these applications.
Keywords :
blades; condition monitoring; data acquisition; fault diagnosis; feature extraction; mechanical engineering computing; signal classification; vibrations; wind turbines; blades; chaotic attractor; data acquisition; fault diagnosis; feature parameters; operational fault feature extraction; vibration signal classification; wind turbines; Blades; Correlation; Fasteners; Feature extraction; Monitoring; Vibrations; Wind turbines;
Conference_Titel :
Control, Automation and Systems Engineering (CASE), 2011 International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4577-0859-6
DOI :
10.1109/ICCASE.2011.5997632