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 |
|
Zarouchas, Dimitrios
Delft University of Technology
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (30/30 displayed)
- 2024Innovative welding integration of acousto-ultrasonic composite transducers onto thermoplastic composite structurescitations
- 2023Intelligent Health Indicators Based on Semi-supervised Learning Utilizing Acoustic Emission Datacitations
- 2023Non-destructive strength prediction of composite laminates utilizing deep learning and the stochastic finite element methodscitations
- 2023Acousto-ultrasonic composite transducers integration into thermoplastic composite structures via ultrasonic welding
- 2023Hierarchical Upscaling of Data-Driven Damage Diagnostics for Stiffened Composite Aircraft Structures
- 2023Intelligent health indicator construction for prognostics of composite structures utilizing a semi-supervised deep neural network and SHM datacitations
- 2023An SHM Data-Driven Methodology for the Remaining Useful Life Prognosis of Aeronautical Subcomponentscitations
- 2023A novel strain-based health indicator for the remaining useful life estimation of degrading composite structurescitations
- 2023Developing health indicators for composite structures based on a two-stage semi-supervised machine learning model using acoustic emission datacitations
- 2023Analysis of Stochastic Matrix Crack Evolution in CFRP Cross-Ply Laminates under Fatigue Loadingcitations
- 2023Delamination Size Prediction for Compressive Fatigue Loaded Composite Structures Via Ultrasonic Guided Wave Based Structural Health Monitoring
- 2022On the Challenges of Upscaling Damage Monitoring Methodologies for Stiffened Composite Aircraft Panelscitations
- 2022Synthesis and characterization of novel eco-epoxy adhesives based on the modified tannic acid for self-healing jointscitations
- 2022Synthesis and characterization of novel eco-epoxy adhesives based on the modified tannic acid for self-healing jointscitations
- 2022Assessing stiffness degradation of stiffened composite panels in post-buckling compression-compression fatigue using guided wavescitations
- 2022Early fatigue damage accumulation of CFRP Cross-Ply laminates considering size and stress level effectscitations
- 2021A Strain-Based Health Indicator for the SHM of Skin-to-Stringer Disbond Growth of Composite Stiffened Panels in Fatiguecitations
- 2021Health monitoring of aerospace structures utilizing novel health indicators extracted from complex strain and acoustic emission datacitations
- 2021A review of experimental and theoretical fracture characterization of bi-material bonded jointscitations
- 2021Fusion-based damage diagnostics for stiffened composite panelscitations
- 2021Health indicators for diagnostics and prognostics of composite aerospace structurescitations
- 2021Damage assessment of a titanium skin adhesively bonded to carbon fiber–reinforced plastic omega stringers using acoustic emissioncitations
- 2020Damage assessment of NCF, 2D and 3D Woven Composites under Compression After Multiple-Impact using Acoustic Emissioncitations
- 2020The effect of temperature on fatigue strength of poly(ether-imide)/multiwalled carbon nanotube/carbon fibers composites for aeronautical applicationcitations
- 2019Compression After Multiple Low Velocity Impacts of NCF, 2D and 3D Woven Compositescitations
- 2019Physics of delamination onset in unidirectional composite laminates under mixed-mode I/II loadingcitations
- 2019Damage characterization of adhesively-bonded Bi-material joints using acoustic emissioncitations
- 2010Numerical failure analysis of composite structures
- 2009Study of the mechanical response of carbon Reinforced concrete beams using Non Destructive Techniques during a four-point bending test
- 2009Study of the crack propagation in carbon reinforced concrete beams during a four-point bending test
Places of action
Organizations | Location | People |
---|
article
Health monitoring of aerospace structures utilizing novel health indicators extracted from complex strain and acoustic emission data
Abstract
The development of health indicators (HI) of diagnostic and prognostic potential from generally uninformative raw sensor data is both a challenge and an essential feature for data‐driven diagnostics and prognostics of composite structures. In this study, new damage‐sensitive features, developed from strains acquired with Fiber Bragg Grating (FBG) and acoustic emission (AE) data, were investigated for their suitability as HIs. Two original fatigue test campaigns (constant and variable amplitude) were conducted on single‐stringer composite panels using appropriate sensors. After an initial damage introduction in the form of either impact damage or artificial disbond, the panels were subjected to constant and variable amplitude compression–compression fatigue tests. Strain sensing using FBGs and AE was employed to monitor the damage growth, which was further verified by phased array ultrasound. Several FBGs were incorporated in special SMARTapes™, which were bonded along the stiffener’s feet to measure the strain field, whereas the AE sensors were strategically placed on the panels’ skin to record the acoustic emission activity. HIs were developed from FBG and AE raw data with promising behaviors for health monitoring of composite structures during service. A correlation with actual damage was attempted by leveraging the measurements from a phased array camera at several time instances throughout the experiments. The developed HIs displayed highly monotonic behaviors while damage accumulated on the composite panel, with moderate prognosability. ; Structural Integrity & Composites