| 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 |
|
Groves, Roger
Delft University of Technology
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (29/29 displayed)
- 2024Shearography With Thermal Loading For Defect Detection Of Small Defects In Cfrp Composites
- 2024Towards hydrogen fueled aircraft
- 2024Advancing Hydrogen Sensing for Sustainable Aviationcitations
- 2023Towards safe shearography inspection of thick composites with controlled surface temperature heatingcitations
- 2022Shearography non-destructive testing of thick GFRP laminatescitations
- 2022Shearography non-destructive testing of a composite ship hull section subjected to multiple impacts
- 2021Optical Material Characterisation of Prepreg CFRP for Improved Composite Inspectioncitations
- 2021Spatially modulated thermal excitations for shearography non-destructive inspection of thick compositescitations
- 2021Modeling and imaging of ultrasonic array inspection of side drilled holes in layered anisotropic mediacitations
- 2020Simulation of ultrasonic beam propagation from phased arrays in anisotropic media using linearly phased multi-Gaussian beamscitations
- 2020A gaussian beam based recursive stiffness matrix model to simulate ultrasonic array signals from multi-layered mediacitations
- 2020Simultaneous temperature-strain measurement in a thin composite panel with embedded tilted Fibre Bragg Grating sensors (PPT)
- 2020Algorithm assessment for layup defect segmentation from laser line scan sensor based image datacitations
- 2019Systematic multiparameter design methodology for an ultrasonic health monitoring system for full-scale composite aircraft primary structurescitations
- 2018Experimental assessment of the influence of welding process parameters on Lamb wave transmission across ultrasonically welded thermoplastic composite jointscitations
- 2018Incorporating Inductive Bias into Deep Learning
- 2018Non-Destructive Testing for Detection, Localization and Quantification of Damage on Composite Structures for Composite Repair Applications
- 2018Full-scale testing of an ultrasonic guided wave based structural health monitoring system for a thermoplastic composite aircraft primary structure
- 2018EXTREME shearographycitations
- 20183.12 Inspection and Monitoring of Composite Aircraft Structurescitations
- 2017Online preventive non-destructive evaluation for automated fibre placement
- 2017Modelling of ultrasonic beam propagation from an array through transversely isotropic fibre reinforced composites using Multi Gaussian beams
- 2017Epoxy-hBN nanocompositescitations
- 2017Advanced signal processing techniques for fibre-optic structural health monitoring
- 2016Online Preventative Non-Destructive Evaluation in Automated Fibre Placement
- 2016Thermal strains in heated Fiber Metal Laminates
- 2016Monitoring chemical degradation of thermally cycled glass-fibre composites using hyperspectral imagingcitations
- 2016Experimental characterisation of Lamb wave propagation through thermoplastic composite ultrasonic welds
- 2016Perspectives on Structural Health Monitoring of Composite Civil Aircraft
Places of action
| Organizations | Location | People |
|---|
conferencepaper
Algorithm assessment for layup defect segmentation from laser line scan sensor based image data
Abstract
The Automated Fiber Placement process is established in the aerospace industry for the production of composite components. This technique places several narrow material strips in parallel. Within current industrial Automated Fiber Placement processes the visual inspection takes typically up to 50% of overall production time. Furthermore, inspection quality highly depends on the inspector. Therefore, automation of visual inspection offers a great improvement potential. To ensure reliable defect detection the segmentation of individual defects must be investigated. For this reason, this paper focusses on an assessment of defect segmentation algorithms. Therefore, 29 structural, statistical and spectral algorithms from related work were assessed, theoretically, using the 12 most relevant criteria as assessed from literature and process requirements. Then, seven most auspicious algorithms were analysed in detail. For reasons of determinism, Neural Network approaches are not part of this paper. Manually labelled prepreg defect images from a laser line scan sensor were used for tests. The test samples contain five defect types with 50 samples of each. Additionally, layups without defects were analysed. It was concluded that Adaptive Thresholding works best for global defect segmentation. The Cell Wise Standard Deviation Thresholding performs also quite well, but is very sensitive to grid size. Feasible algorithms perform reliable defect segmentation for layed up material. ; Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. ; Structural Integrity & Composites