693.932 PEOPLE
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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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Fiedler, Bodo
Hamburg University of Technology
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (39/39 displayed)
- 2024Comprehensive evaluation of CFRP laminates using NDT methods for aircraft applications
- 2024Using thermokinetic methods to enhance properties of epoxy resins with amino acids as biobased curing agents by achieving full crosslinkingcitations
- 2023Monitoring of water absorption and its effects on mechanical performance of thick GFRP structures by integrated smart sensors
- 2023Herausforderungen dickwandiger, duroplastischer Faser-Kunststoff-Verbunde in der Herstellung sowie mechanischen und zerstörungsfreien Prüfung - Ein Reviewcitations
- 2023Time, temperature and water aging failure envelope of thermoset polymerscitations
- 2023Reversible and irreversible effects on the epoxy GFRP fiber-matrix interphase due to hydrothermal agingcitations
- 2022Fragmentation of beaded fibres in a composite
- 2022Fully-integrated carbon nanotube epoxy film sensors for strain sensing in GFRP
- 2021Weak adhesion detection – enhancing the analysis of vibroacoustic modulation by machine learningcitations
- 2021Steel foil reinforcement for high performance bearing strength in Thin‐Ply composites
- 2021Damage tolerance and notch sensitivity of bio-inspired thin-ply Bouligand structurescitations
- 2021Fatigue and fatigue after impact behaviour of Thin- and Thick-Ply composites observed by computed tomography
- 2021Fatigue and fatigue after impact behaviour of Thin- and Thick-Ply composites observed by computed tomographycitations
- 2020Impact of temperature on LVI-damage and tensile and compressive residual strength of CFRPcitations
- 2020Nanocomposites with p- and n-Type Conductivity Controlled by Type and Content of Nanotubes in Thermosets for Thermoelectric Applicationscitations
- 2019Fracture, failure and compression behaviour of a 3D interconnected carbon aerogel (Aerographite) epoxy compositecitations
- 2019Low-velocity impact response of friction riveted joints for aircraft application
- 2019Evaluation and modeling of the fatigue damage behavior of polymer composites at reversed cyclic loadingcitations
- 2019Systematically Designed Periodic Electrophoretic Deposition for Decorating 3D Carbon-Based Scaffolds with Bioactive Nanoparticlescitations
- 2019Biomimetic Carbon-Fiber Systems Engineering: A Modular Design Strategy to Generate Biofunctional Composites from Graphene and Carbon Nanofibers
- 2019Evaluation and Modeling of the Fatigue Damage Behavior of Polymer Composites at Reversed Cyclic Loading
- 2019Maximizing bearing fatigue lifetime and CAI capability of fibre metal laminates by nanoscale sculptured Al pliescitations
- 2019Biomimetic Carbon Fiber Systems Engineeringcitations
- 2019Individual CdS-covered aerographite microtubes for room temperature VOC sensing with high selectivitycitations
- 2019Tailored crystalline width and wall thickness of an annealed 3D carbon foam composites and its mechanical property
- 2019Development of a colored GFRP with antistatic properties
- 2018Hierarchical aerographite 3D flexible networks hybridized by InP micro/nanostructures for strain sensor applicationscitations
- 2018Hierarchical aerographite 3D flexible networks hybridized by InP micro/nanostructures for strain sensor applicationscitations
- 2018Fundamentals of the temperature-dependent electrical conductivity of a 3D carbon foam—Aerographite
- 2018Frequency or amplitude? : Rheo-electrical characterization of carbon nanoparticle filled epoxy systemscitations
- 2018Development of a colored GFRP with antistatic propertiescitations
- 20173D carbon networks and their polymer compositescitations
- 2017Compression fracture of CFRP laminates containing stress intensifications
- 2017Growth model of a carbon based 3D structure (Aerographite) and electrical/mechanical properties of composites
- 2017Online monitoring of surface cracks and delaminations in carbon fiber/epoxy composites using silver nanoparticle based ink
- 2017Fatigue properties of CFRP cross-ply laminates with tailored few layer graphene enhancement
- 2017Influence of carbon nanoparticle modification on the mechanical and electrical properties of epoxy in small volumes
- 2016Fracture, failure and compression behaviour of a 3D interconnected carbon aerogel (Aerographite) epoxy compositecitations
- 2016Electro-mechanical piezoresistive properties of three dimensionally interconnected carbon aerogel (Aerographite)-epoxy compositescitations
Places of action
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document
Weak adhesion detection – enhancing the analysis of vibroacoustic modulation by machine learning
Abstract
Adhesive bonding is a well-established technique for composite materials. Despite advanced surface treatments and preparations, surface contamination and application errors still occur, resulting in localised areas with a reduced adhesion. The dramatic reduction of the bond strength limits the applicability of adhesive bonds and hampers further industrial adaptation. This study aims to detect weak-bonds due to manufacturing errors or contamination by analysing and interpreting the vibroacoustic modulation signals with the aid of machine learning. An ultrasonic signal is introduced into the specimen by a piezoceramic actuator and modulated through a low frequency vibration excited by a servo-hydraulic testing system. Tested samples are single-lap shear specimens, according to ASTM D5868-01, with artificial circular debonding areas introduced as PTFE-films or a release agent contamination. It is shown that an artificial neural network can identify various defects in the bonded joint robustly and is able to predict residual strengths and hence demonstrates great potential for non-destructive testing of adhesive joints.