| People | Locations | Statistics |
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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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Steinbild, Philip Johannes
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (12/12 displayed)
- 2024Comparative study of fiber Bragg sensors in remote and direct configuration for impact detection
- 2024Entwicklung eines Systems zur Messung von Kräften und Kraftverteilungen an einem Wurfstuhl für den paralympischen Wurf und Stoß – FORCEAT
- 2024Development of a smart implant for monitoring spinal stabilization using a rod-integrated measurement system
- 2023Integration of sensors in sandwich composites for the detection of structural damage
- 2023Spatially resolved strain measurement at meter scale using a carbon fiber based strain sensor and artificial neural networks
- 2022Rückwirkungsarmes Messsystem mit drahtloser Datenübertragung zur Messung von Kräften und Biegungen an einem Langlauf-Skistock
- 2021Entwicklung eines mobilen, rückwirkungsfreien Monitoringsystems zur dehnungsbasierten Erfassung von Belastungen am Skistock - SmaPole
- 2021Load monitoring for sailplanes utilizing an innovative carbon fibre-based, spatially resolved strain sensor
- 2021Functional Design Employing Miniaturized Electronics with Wireless Signal Provision to a Smartphone for a Strain-Based Measuring System for Ski Polescitations
- 2019Regionales Innovationskonzept "WIR!-DigiT" - Zentrum für vernetzte digitale Produktoptimierung durch Lebensphasen-übergreifende virtuelle Zwillinge
- 2018Cyber-physische Systeme im Leistungssport auf der Basis vernetzter Sportgeräte – Anwendungsfall Skistock im Projekt SMAPOLE
- 2018On detecting kissing bonds in adhesively bonded joints using electric time domain reflectometry
Places of action
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document
Spatially resolved strain measurement at meter scale using a carbon fiber based strain sensor and artificial neural networks
Abstract
Life cycle optimization, maintenance planning and adaptive control systems in fiber-reinforced structures such as aircraft wings require the monitoring of loads and stresses during operation. State of the art systems using strain gauges can measure strains at limited numbers of discrete points, while systems based on fiber optic time domain reflectometry require complex and cost intensive evaluation units. A novel sensor based on electrical time domain reflectometry (ETDR) allows to acquire information about the spatial distribution of strain alonga fractured carbon fiber (CF) embedded in a composite structure. This sensor concept has been investigated in previous studies with specimens up to 60 mm in length. Based on this work, a demonstrator with an improved sensor layout and two embedded sensors of 1 m length is developed. A shallow feed-forward network and a convolutional neural network are compared regarding their ability to infer strain profiles from measured ETDR reflectograms. The simultaneous evaluation of two sensors with a convolutional neural network allowed the inference of strain distributions with a good generalization ability.