scholarly journals Fatigue Test Design: Scenarios for Biaxial Fatigue Testing of a 60-Meter Wind Turbine Blade

2016 ◽  
Author(s):  
Nathan Post
Keyword(s):  
Wind Turbine ◽  
Fatigue Test ◽  
Turbine Blade ◽  
Fatigue Testing ◽  
Wind Turbine Blade ◽  
Test Design ◽  
Biaxial Fatigue

Study of Fatigue Test Loading Spectrum for Wind Turbine Blade

2014 ◽  
Vol 889-890 ◽  
pp. 221-224
Author(s):  
Gao Hua Liao ◽  
Jian Zhong Wu ◽  
Yong Jun Yu
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Fatigue Test ◽  
Turbine Blade ◽  
Time History ◽  
Wind Load ◽  
Wind Turbine Blade ◽  
Fatigue Life Analysis ◽  
Test Loading ◽  
Loading Spectrum

According to the principle of equivalent, the approach to draw up the fatigue test loading spectrum of wind turbine blade is presented. Analysis of wind load characteristics, based on ARMA (Autoregressive Moving Average Model) for the simulation of wind speed, wind load simulation example is given. Using Bladed software, the wind speed-time history is converted to a moment-time history that is the equivalent of blade root.Using data compression technology and the rain flow counting algorithm, load represented by a 2D matrix examples is given.The one-dimensional symmetry loading spectrum draw up, the complexity can be simplified, and provides the necessary foundation for fatigue life analysis.

Fatigue Failure of a Composite Wind Turbine Blade at the Trailing Edge

2018 ◽  
Vol 382 ◽  
pp. 191-195 ◽  
Author(s):  
Zu Jin Pan ◽  
Jian Zhong Wu ◽  
Jian Liu ◽  
Xin Hua Zhao
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Failure Modes ◽  
Fatigue Testing ◽  
Turbine Blades ◽  
Local Stress ◽  
Wind Turbine Blade ◽  
Trailing Edge ◽  
Balsa Wood ◽  
Abnormal Sound

The downtime problem of wind turbine increases due to fatigue damage of wind turbine blades, which is even more crucial in the larger blades. One of the critical failure modes is the blade trailing edge failure, which can result in the trailing edge joint cracked. In this paper, we experienced that abnormal sound was happened in the trailing edge at the cross-section in the max chord during fatigue testing of a 2 MW full-scale wind turbine blade according to IEC61400-23. Through the conditional monitoring of the trailing edge, the delamination between GFRP and balsa wood is caused by stress concentration. The abnormal sound is happened due to GFRP beat the balsa wood when the blade vibrates in the edgewise direction. Moreover, the sound is amplified because the introduction of air due to the delamination. The local stress distribution and stability factors are computed through FEM methods, the program that increasing the core materials in the trailing edge is proposed. Therefore the structure reliability in the trailing edge is improved.

scholarly journals Joint excitation synchronization characteristics of fatigue test for offshore wind turbine blade

AIP Advances ◽  
2018 ◽  
Vol 8 (2) ◽  
pp. 025112 ◽  
Author(s):  
Lei-an Zhang ◽  
Xiang-yong Yu ◽  
Xiu-ting Wei ◽  
Wei-sheng Liu
Keyword(s):  
Wind Turbine ◽  
Fatigue Test ◽  
Turbine Blade ◽  
Wind Turbine Blade ◽  
Offshore Wind ◽  
Offshore Wind Turbine

scholarly journals The Study of Wind Turbine Blade Fatigue Test

2021 ◽  
Vol 293 ◽  
pp. 02024
Author(s):  
Jiaqi Zheng ◽  
Qiming Yu ◽  
Botao Zhu ◽  
Changqing Wu ◽  
Yiling Huang ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Fatigue Test ◽  
Turbine Blade ◽  
Excitation Amplitude ◽  
Wind Turbine Blade ◽  
Excitation Mode ◽  
Practical Operation ◽  
Important Means ◽  
Feasible Solutions ◽  
The Relationship

The fatigue test of wind turbine blade is an important means to verify the fatigue life of wind turbine blade. This paper analyses the problems existing in the fatigue test of wind turbine blade, focuses on the excitation mode, the relationship between excitation amplitude and vibration frequency and the vibration principle, and puts forward feasible solutions in practical operation.

Health assessment and management of wind turbine blade based on the fatigue test data

2017 ◽  
Vol 75 ◽  
pp. 205-214 ◽  
Author(s):  
Xuezong Bai ◽  
Zongwen An ◽  
Yunfeng Hou ◽  
Qiang Ma
Keyword(s):  
Wind Turbine ◽  
Fatigue Test ◽  
Turbine Blade ◽  
Test Data ◽  
Health Assessment ◽  
Wind Turbine Blade

scholarly journals Full-Scale Fatigue Testing of a Wind Turbine Blade in Flapwise Direction and Examining the Effect of Crack Propagation on the Blade Performance

Materials ◽  
2017 ◽  
Vol 10 (10) ◽  
pp. 1152 ◽  
Author(s):  
Othman Al-Khudairi ◽  
Homayoun Hadavinia ◽  
Christian Little ◽  
Gavin Gillmore ◽  
Peter Greaves ◽  
...  
Keyword(s):  
Crack Propagation ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Fatigue Testing ◽  
Full Scale ◽  
Wind Turbine Blade

An experimental investigation into passive acoustic damage detection for structural health monitoring of wind turbine blades

2020 ◽  
Vol 19 (6) ◽  
pp. 1711-1725 ◽  
Author(s):  
Jaclyn Solimine ◽  
Christopher Niezrecki ◽  
Murat Inalpolat
Keyword(s):  
Signal Processing ◽  
Structural Health Monitoring ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Health Monitoring ◽  
Fatigue Testing ◽  
Turbine Blades ◽  
Wind Turbine Blade ◽  
Wind Turbine Blades ◽  
Structural Health

This article details the implementation of a novel passive structural health monitoring approach for damage detection in wind turbine blades using airborne sound. The approach utilizes blade-internal microphones to detect trends, shifts, or spikes in the sound pressure level of the blade cavity using a limited network of internally distributed airborne acoustic sensors, naturally occurring passive system excitation, and periodic measurement windows. A test campaign was performed on a utility-scale wind turbine blade undergoing fatigue testing to demonstrate the ability of the method for structural health monitoring applications. The preliminary audio signal processing steps used in the study, which were heavily influenced by those methods commonly utilized in speech-processing applications, are discussed in detail. Principal component analysis and K-means clustering are applied to the feature-space representation of the data set to identify any outliers (synonymous with deviations from the normal operation of the wind turbine blade) in the measurements. The performance of the system is evaluated based on its ability to detect those structural events in the blade that are identified by making manual observations of the measurements. The signal processing methods proposed within the article are shown to be successful in detecting structural and acoustic aberrations experienced by a full-scale wind turbine blade undergoing fatigue testing. Following the assessment of the data, recommendations are given to address the future development of the approach in terms of physical limitations, signal processing techniques, and machine learning options.

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