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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Neunkirchen, Stefan
FH JOANNEUM University of Applied Sciences
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Publications (4/4 displayed)
- 2023Effect of Binder Activation on in-Plane Capillary Flow in Multilayer Stacks of Carbon Fiber Fabrics
- 2021Instrumentation of an Inspection Test Rig for Geometry Measurement of Fiber Bundles in Automated Composite Manufacturingcitations
- 2021Tack measurement of bindered rovings for the dry fiber winding processcitations
- 2021Instrumentation of a Roving Inspection Test Rig with Surface Geometry Measurement of Fiber Bundlescitations
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document
Instrumentation of a Roving Inspection Test Rig with Surface Geometry Measurement of Fiber Bundles
Abstract
The major advantage of products made from composite materials, such as carbon fiber reinforced polymers (CFRP), is given by their superior weight-specific, mechanical properties such as strength and stiffness. These properties can be weakened by defects induced in the manufacturing process. In dry fiber filament winding, online detection and analysis of the processed fiber bundle geometry is a key factor for the quality assurance of the final part. In this work, the instrumentation and data evaluation for determining the surface geometry of fiber bundles by means of a light sectioning sensor was examined. Profiles of glass fibers were measured continuously in a specifically developed inspection test rig. By application of an interactive polynomial fitting algorithm, data segmentation of object and base line was robustly achieved on varying background conditions. In addition, unwanted defects as well as lateral movement of the fiber bundles were reliably detected. The information revealed by the proposed algorithm provides the basis for robust online monitoring of fiber bundle geometry in highly automated composite manufacturing processes.