People | Locations | Statistics |
---|---|---|
Naji, M. |
| |
Motta, Antonella |
| |
Aletan, Dirar |
| |
Mohamed, Tarek |
| |
Ertürk, Emre |
| |
Taccardi, Nicola |
| |
Kononenko, Denys |
| |
Petrov, R. H. | Madrid |
|
Alshaaer, Mazen | Brussels |
|
Bih, L. |
| |
Casati, R. |
| |
Muller, Hermance |
| |
Kočí, Jan | Prague |
|
Šuljagić, Marija |
| |
Kalteremidou, Kalliopi-Artemi | Brussels |
|
Azam, Siraj |
| |
Ospanova, Alyiya |
| |
Blanpain, Bart |
| |
Ali, M. A. |
| |
Popa, V. |
| |
Rančić, M. |
| |
Ollier, Nadège |
| |
Azevedo, Nuno Monteiro |
| |
Landes, Michael |
| |
Rignanese, Gian-Marco |
|
Mcgugan, Malcolm
Technical University of Denmark
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (21/21 displayed)
- 2025Acoustic emission data analytics on delamination growth in a wind turbine blade under full-scale cyclic testingcitations
- 2024Understanding Fatigue Delamination Crack Growth in a Wind Turbine Rotor Blade Through an Element Testing
- 2021Fatigue testing of a 14.3 m composite blade embedded with artificial defects – damage growth and structural health monitoringcitations
- 2018Impact fatigue damage of coated glass fibre reinforced polymer laminatecitations
- 2018Impact fatigue damage of coated glass fibre reinforced polymer laminatecitations
- 2018Development of Single Point Impact Fatigue Tester (SPIFT)
- 2018Development of Single Point Impact Fatigue Tester (SPIFT)
- 2016Fibre Bragg Grating Sensor Signal Post-processing Algorithm: Crack Growth Monitoring in Fibre Reinforced Plastic Structurescitations
- 2015Crack Detection in Fibre Reinforced Plastic Structures Using Embedded Fibre Bragg Grating Sensors: Theory, Model Development and Experimental Validationcitations
- 2015Structural health monitoring method for wind turbine trailing edge: Crack growth detection using Fibre Bragg Grating sensor embedded in composite materials
- 2015Crack Growth Monitoring by Embedded Optical Fibre Bragg Grating Sensors: Fibre Reinforced Plastic Crack Growing Detectioncitations
- 2015Embedded Fibre Bragg Grating Sensor Response Model: Crack Growing Detection in Fibre Reinforced Plastic Materialscitations
- 2015Damage tolerant design and condition monitoring of composite material and bondlines in wind turbine blades: Failure and crack propagation
- 2015Crack growth monitoring in composite materials using embedded optical Fiber Bragg Grating sensor
- 2013Bondlines – Online blade measurements (October 2012 and January 2013)
- 2011Development and Testing of an Acoustoultrasonic Inspection Device for Condition Monitoring of Wind Turbine Blades
- 2010Full Scale Test of SSP 34m blade, edgewise loading LTT:Data Report 1
- 2008Full Scale Test of a SSP 34m boxgirder 2:Data report
- 2008Fundamentals for remote condition monitoring of offshore wind turbines
- 2008Full Scale Test of a SSP 34m boxgirder 2
- 2006Detecting and identifying damage in sandwich polymer composite by using acoustic emission
Places of action
Organizations | Location | People |
---|
article
Fatigue testing of a 14.3 m composite blade embedded with artificial defects – damage growth and structural health monitoring
Abstract
Understanding fatigue damage growth of composite wind turbine blades is an essential step towards reliable structural health monitoring (SHM) and accurate lifetime prediction. This study presents a comprehensive experimental investigation into damage growth within a full-scale composite wind turbine blade under fatigue loading. The blade has artificial defects embedded to initiate damage growth. The damages are detected and monitored using Infrared (IR) thermography, Digital Image Correlation (DIC), and Acoustic Emission (AE). Steady damage growth and imminent structural failure are identified, demonstrating the effectiveness of these techniques to detect subsurface damages. New experimental observations include cyclic buckling of a trailing edge region and tapping and rubbing between the shear web and spar cap, both damages due to adhesive joint debonds. These observations highlight the necessity and the complexity of reliable modeling of nonlinear structural behavior on a large scale in order to predict local fatigue crack growth.