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 |
|
Sierra, Julian
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (11/11 displayed)
- 2021Toward Structural Health Monitoring of Civil Structures Based on Self-Sensing Concrete Nanocompositescitations
- 2020In-flight and wireless damage detection in a UAV composite wing using fiber optic sensors and strain field pattern recognitioncitations
- 2019Artificial Intelligence Metamodeling Approach to Design Smart Composite Laminates with Bend-Twist Couplingcitations
- 2019Synthesis and characterization of cement/carbon-nanotube composite for structural health monitoring applicationscitations
- 2019Structural design and manufacturing process of a low scale bio-inspired wind turbine bladescitations
- 2018Structural health monitoring using carbon nanotube/epoxy composites and strain-field pattern recognition
- 2018Damage detection in composite aerostructures from strain and telemetry data fusion by means of pattern recognition techniques
- 2017Structural health monitoring on an unmanned aerial vehicle wing's beam based on fiber Bragg gratings and pattern recognition techniquescitations
- 2016Damage and nonlinearities detection in wind turbine blades based on strain field pattern recognition. FBGs, OBR and strain gauges comparisoncitations
- 2014A robust procedure for damage identification in a lattice spacecraft structural element by mean of Strain field pattern recognition techniques
- 2014Strain measurements and damage detection in large composite structures by fiber optics sensors
Places of action
Organizations | Location | People |
---|
document
A robust procedure for damage identification in a lattice spacecraft structural element by mean of Strain field pattern recognition techniques
Abstract
<p>A high stiffness and low weight lattice structure for launcher applications made with high modulus carbon fiber was manufactured by EADS CASA Space by using a new cost efficient fiber placement technology. The structure consisted of a composite lattice of intertwined, unidirectional carbon fiber bars. Several Fiber Bragg Gratings (FBGs) were bonded along these bars in order to measure strain during different tests performed on the structure. A robust procedure for defect detection based on Principal Component Analysis (PCA) and strain field pattern recognition techniques was used in order to identify different defects induced in the structure during static testing conducted until fracture. A test campaign of smaller, iso-grid structures was conducted with the aim of studying the sensitivity to detect small defects in the lattice structure. A PCA model was built for the healthy structure. Subsequently, different known damage conditions were projected into the PCA model (baseline). From this projection, various damage indices and detection thresholds were calculated. The results showed that even small damages located far away from the sensors could be detected by this technique.</p>