Static test of the embedded fiber Bragg gratings composite wind turbine blades

2011 ◽  
Author(s):  
Zhichun Zhang ◽  
Zhong Huang ◽  
Yanjiu Liu ◽  
Jinsong Leng
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Fiber Bragg Gratings ◽  
Bragg Gratings ◽  
Wind Turbine Blades ◽  
Static Test

Acoustic Emission Monitoring of Small Wind Turbine Blades

2002 ◽  
Author(s):  
P. A. Joosse ◽  
M. J. Blanch ◽  
A. G. Dutton ◽  
D. A. Kouroussis ◽  
T. P. Philippidis ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Wind Turbine ◽  
Fibre Composite ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Static Test ◽  
Damage Propagation ◽  
Test Methodology ◽  
Certification Procedure ◽  
Damage Processes

Wind turbine blade certification tests, comprising a static test, a fatigue test, and finally a residual strength test, often involve sudden audible cracking sounds from somewhere within the blade, without the operators being able to locate the noise source, or to determine whether damage (minor or major) has occurred. A current EC-funded research project is looking at the possibility of using acoustic emission (AE) monitoring during testing of fibre composite blades to detect such events and assess the blade condition. AE can both locate and characterise damage processes in blades, starting with non-audible signals occurring due to damage propagation at relatively low loads. The test methodology is discussed in the context of the blade certification procedure and results are presented from a series of static and fatigue blade tests to failure in the laboratory. Inferences are drawn about small differences in the manufacture of the nominally identical blades and conclusions are presented for the application of the methodology.

scholarly journals GA-BP Neural Network-Based Strain Prediction in Full-Scale Static Testing of Wind Turbine Blades

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1026 ◽  
Author(s):  
Zheng Liu ◽  
Xin Liu ◽  
Kan Wang ◽  
Zhongwei Liang ◽  
José A.F.O. Correia ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Back Propagation ◽  
Health Assessment ◽  
Prediction Method ◽  
Full Scale ◽  
Wind Turbine Blades ◽  
Static Test ◽  
Static Testing ◽  
Input Variables

This paper proposes a strain prediction method for wind turbine blades using genetic algorithm back propagation neural networks (GA-BPNNs) with applied loads, loading positions, and displacement as inputs, and the study can be used to provide more data for the wind turbine blades’ health assessment and life prediction. Among all parameters to be tested in full-scale static testing of wind turbine blades, strain is very important. The correlation between the blade strain and the applied loads, loading position, displacement, etc., is non-linear, and the number of input variables is too much, thus the calculation and prediction of the blade strain are very complex and difficult. Moreover, the number of measuring points on the blade is limited, so the full-scale blade static test cannot usually provide enough data and information for the improvement of the blade design. As a result of these concerns, this paper studies strain prediction methods for full-scale blade static testing by introducing GA-BPNN. The accuracy and usability of the GA-BPNN prediction model was verified by the comparison with BPNN model and the FEA results. The results show that BPNN can be effectively used to predict the strain of unmeasured points of wind turbine blades.

Experiments of Wind Turbine Blades with Rocket Triggered Lightning

2009 ◽  
Vol 129 (5) ◽  
pp. 689-695
Author(s):  
Masayuki Minowa ◽  
Shinichi Sumi ◽  
Masayasu Minami ◽  
Kenji Horii
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Triggered Lightning

Folding of flexible hinges for aircraft wingtips and wind turbine blades

2021 ◽  
Author(s):  
Aileen G. Bowen Perez ◽  
Giovanni Zucco ◽  
Paul Weaver
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Wind Turbine Blades

Evaluation of the influence of wind speed and angle of attack on the aerodynamic effect of wind turbine blades

2017 ◽  
Author(s):  
Salete Alves ◽  
Luiz Guilherme Vieira Meira de Souza ◽  
Edália Azevedo de Faria ◽  
Maria Thereza dos Santos Silva ◽  
Ranaildo Silva
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Turbine Blades ◽  
Angle Of Attack ◽  
Wind Turbine Blades ◽  
Aerodynamic Effect
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