An Identification Method of Appearances and Expansion of Fatigue Crack in the Wind Turbine Blade Based on Fractal Feature

2012 ◽  
Vol 591-593 ◽  
pp. 2123-2126
Author(s):  
Bo Zhou ◽  
Chang Zheng Chen ◽  
Quan Gu ◽  
Huan Liu
Keyword(s):  
Acoustic Emission ◽  
Fractal Dimension ◽  
Fatigue Crack ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Correlation Dimension ◽  
Wind Turbine Blade ◽  
Crack Identification ◽  
Simplified Method ◽  
Fatigue Experiment

In this work an efficient and simplified method for crack identification in wind turbine blade has been developed based on fractal dimension. Firstly, the algorithm is studied on the calculation of the correlation dimension of acoustic emission signals, and an analysis of these equations makes it possible to identify cracks. Then it turns out that the complexity could vary with different crack expansion conditions, i.e. reduction and augmentation of the correlation dimension due to the occurrence of a crack by the fatigue experiment. Finally, the proposed detection methodology is compared to wavelet analysis. It is testified that the method exploits both the typical steady expansion of the crack and the appearance phenomenon due to the presence of crack.

Damage mode identification of composite wind turbine blade under accelerated fatigue loads using acoustic emission and machine learning

2019 ◽  
Vol 19 (4) ◽  
pp. 1092-1103 ◽  
Author(s):  
Pengfei Liu ◽  
Dong Xu ◽  
Jingguo Li ◽  
Zhiping Chen ◽  
Shuaibang Wang ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Wind Turbine Blade ◽  
Mode Identification ◽  
Emission Signal ◽  
Composite Blade ◽  
Acoustic Emission Sensors ◽  
Safety Precaution ◽  
Fatigue Loads

This article studies experimentally the damage behaviors of a 59.5-m-long composite wind turbine blade under accelerated fatigue loads using acoustic emission technique. First, the spectral analysis using the fast Fourier transform is used to study the components of acoustic emission signals. Then, three important objectives including the attenuation behaviors of acoustic emission waves, the arrangement of sensors as well as the detection and positioning of defect sources in the composite blade by developing the time-difference method among different acoustic emission sensors are successfully reached. Furthermore, the clustering analysis using the bisecting K-means method is performed to identify different damage modes for acoustic emission signal sources. This work provides a theoretical and technique support for safety precaution and maintaining of in-service blades.

Acoustic Emission Attenuation and Source Location of Resin Matrix for Wind Turbine Blade Composites

2014 ◽  
Vol 912-914 ◽  
pp. 36-39 ◽  
Author(s):  
Yan Rong Pang ◽  
Zhi Hui Lv ◽  
Xiao Min Liang ◽  
Han Chang Chai ◽  
Ruo Chen Liu ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Source Location ◽  
Wind Turbine Blade ◽  
Resin Matrix ◽  
Destructive Testing ◽  
Testing Technology ◽  
Ae Signal ◽  
The One

In recent years, acoustic emission (AE) testing technology is the one of the most important non-destructive testing (NDT) methods. The characteristics can be described by AE signals, including the location, nature and severity. In order to obtain the basic data for monitoring the wind turbine blade composite structure, the experiment adopted Φ0.5 mm lead pencil as artificial acoustic emission source and measured AE parameters, attenuation and source location of resin matrix for wind turbine blade. This paper introduced linear location and two-dimensional positioning technology of time arrival location method about the burst AE signal. The result shows that the location of AE source basically reflects the location of stimulation AE source, the location of AE source for resin matrix can agree well with the simulated location of AE source, the more close to the middle area, the more accurate location.

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