Fault Diagnosis of Industrial Wind Turbine Blade Bearing Using Acoustic Emission Analysis

2020 ◽  
Vol 69 (9) ◽  
pp. 6630-6639 ◽  
Author(s):  
Zepeng Liu ◽  
Xuefei Wang ◽  
Long Zhang
Keyword(s):  
Acoustic Emission ◽  
Fault Diagnosis ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Wind Turbine Blade ◽  
Emission Analysis ◽  
Acoustic Emission Analysis

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.

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.

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