
Damage identification of wind turbine blade based on dynamic characteristics
Author(s) -
Yu Gu,
Jing Feng,
Baohua Jia
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1303/1/012030
Subject(s) - blade (archaeology) , turbine blade , vibration , structural engineering , modal analysis , finite element method , turbine , modal , matlab , blade element momentum theory , computer science , engineering , materials science , acoustics , mechanical engineering , composite material , physics , operating system
The wind turbine blade is an elongated structure composed of composite materials. Due to the harsh working environment and the vibration and deformation during operation, the blade is easily damaged, which seriously affects the smooth operation of the wind turbine, and has great potential safety hazards. The finite element software ANSYS is used to study the vibration characteristics under the condition of blade rotation, and different damage modal analysis can be carried out for different positions. The BP neural network is established by MATLAB to quantify the damage degree of the blade. The analysis results show that the damage and damage degree can be recognized by the change of natural frequency before and after the damage of the blade. The damage location can be identified by change rate of strain mode before and after the damage of the blade. The damage degree of the blade can be quantified and judged. The relative error rate is between -4.36% to 2.73%, and the recognition effect is more accurate.