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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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Pierce, Stephen
University of Strathclyde
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (51/51 displayed)
- 20243-Dimensional residual neural architecture search for ultrasonic defect detectioncitations
- 2023Flexible and automated robotic multi-pass arc welding
- 2023Application of eddy currents for inspection of carbon fibre composites
- 2023Application of machine learning techniques for defect detection, localisation, and sizing in ultrasonic testing of carbon fibre reinforced polymers
- 2023In-process non-destructive evaluation of metal additive manufactured components at build using ultrasound and eddy-current approachescitations
- 2023Mapping SEARCH capabilities to Spirit AeroSystems NDE and automation demand for composites
- 2023Using neural architecture search to discover a convolutional neural network to detect defects From volumetric ultrasonic testing data of composites
- 2023Phased array inspection of narrow-gap weld LOSWF defects for in-process weld inspection
- 2023Driving towards flexible and automated robotic multi-pass arc welding
- 2022Transfer learning for classification of experimental ultrasonic non-destructive testing images from synthetic data
- 2022Mechanical stress measurement using phased array ultrasonic system
- 2022Towards ultrasound-driven, in-process monitoring & control of GTA welding of multi-pass welds for defect detection & prevention
- 2022Automated bounding box annotation for NDT ultrasound defect detection
- 2022Multi-sensor electromagnetic inspection feasibility for aerospace composites surface defects
- 2022Investigating ultrasound wave propagation through the coupling medium and non-flat surface of wire + arc additive manufactured components inspected by a PAUT roller-probe
- 2022Automated multi-modal in-process non-destructive evaluation of wire + arc additive manufacturing
- 2022Towards real-time ultrasound driven inspection and control of GTA welding processes for high-value manufacturing
- 2022Dual-tandem phased array inspection for imaging near-vertical defects in narrow gap welds
- 2022In-process non-destructive evaluation of wire + arc additive manufacture components using ultrasound high-temperature dry-coupled roller-probe
- 2022Automated real time eddy current array inspection of nuclear assetscitations
- 2021Feed forward control of welding process parameters through on-line ultrasonic thickness measurementcitations
- 2021A cost-function driven adaptive welding framework for multi-pass robotic weldingcitations
- 2021Non-contact in-process ultrasonic screening of thin fusion welded jointscitations
- 2020In-process calibration of a non-destructive testing system used for in-process inspection of multi-pass weldingcitations
- 2020Machine learning at the interface of structural health monitoring and non-destructive evaluationcitations
- 2020Quantifying impacts on remote photogrammetric inspection using unmanned aerial vehiclescitations
- 2020Laser-assisted surface adaptive ultrasound (SAUL) inspection of samples with complex surface profiles using a phased array roller-probe
- 2019Ultrasonic phased array inspection of wire + arc additive manufacture samples using conventional and total focusing method imaging approachescitations
- 2019Electromagnetic acoustic transducers for guided-wave based robotic inspection
- 2019A probabilistic compressive sensing framework with applications to ultrasound signal processingcitations
- 2019Ultrasonic phased array inspection of a Wire + Arc Additive Manufactured (WAAM) sample with intentionally embedded defectscitations
- 2019Towards guided wave robotic NDT inspection
- 2018Machining-based coverage path planning for automated structural inspectioncitations
- 2018Ultrasonic phased array inspection of wire plus arc additive manufacture (WAAM) samples using conventional and total focusing method (TFM) imaging approaches
- 2016Investigation of synthetic aperture methods in ultrasound surface imaging using elementary surface typescitations
- 2016Robotic ultrasonic testing of AGR fuel claddingcitations
- 2016Conformable eddy current array deliverycitations
- 2016Robotic path planning for non-destructive testing - a custom MATLAB toolbox approachcitations
- 2014Automatic ultrasonic robotic arraycitations
- 2014Robotic path planning for non-destructive testing of complex shaped surfaces
- 2013The feasibility of synthetic aperture guided wave imaging to a mobile sensor platformcitations
- 2012Features for damage detection with insensitivity to environmental and operational variationscitations
- 2011Some experimental observations on the detection of composite damage using lamb wavescitations
- 2011On impact damage detection and quantification for CFRP laminatescitations
- 2010A comparison of methods used to predict the vibrational energy required for a reliable thermosonic inspection
- 2010Monitoring crack propagation in turbine blades caused by thermosonic inspection
- 2008Damage localisation in a stiffened composite panelcitations
- 2007Damage detection using stress waves and multivariate statistics, an experimental case study of an aircraft componentcitations
- 2007Damage location in a stiffened composite panel using Lamb waves and neural networks
- 2006On the reproducibility of transducer coupling for acoustic emission testing
- 2001On the long-term stability of normal condition for damage detection in a composite panel
Places of action
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document
Multi-sensor electromagnetic inspection feasibility for aerospace composites surface defects
Abstract
UK's presence at the forefront of composite manufacturing in Europe has never been more important provided how vital these structures are for i) slowing the climate change through reduction of fuel consumption and carbon footprint in different industries, and ii) development of wind and tidal blades to generate cleaner energy to achieve the net-zero target by the middle of the century. Therefore, the composite technology, Carbon Fibre Reinforced Polymers (CFRP) in particular, has been dominating the aerospace, energy, and defense industries, and this trend is expected to grow in the years to come. Non-Destructive Evaluation (NDE) is essential during manufacturing: to identify any defects early in the process as, if defects remain undetected, they could have far-reaching implications for the cost of scraped/repaired parts and the safety of final components, and ii) at later stages of manufacturing and post-manufacturing: to ensure the quality, integrity, and fitness for service of these safetycritical components. Although Ultrasound Testing (UT) has been predominantly used for inspection CFRPs owing to its excellent performance for bulk NDE inspections, the method is not sufficiently sensitive to all defect types occurring in such components. Ultrasonic waves transmitted using array probes on CFRP components mainly interact with defects that are extended perpendicularly to the direction of the wave propagation such as delamination. The technique does not offer sufficient sensitivity for the detection of shallow and narrow surface defects commonly created by matrix transversal cracking and barely visible impact damage mechanisms.<br/>The compound CFRP gives rise to the mixed electromagnetic properties where highly conductive carbon fibres are molded in a dielectric resin matrix. This provides a unique opportunity to explore the potential of electromagnetic NDE sensing modalities such as Eddy Currents (EC) and electrical Capacitance Imaging (CI) for inspection of surface defects. Accordingly, this feasibility study was aimed at investigating the design, automated robotic delivery, and performance assessment of different sensor technologies for the detection of surface defects through experiments. To this end, machined surface defects were fabricated in a CFRP sample. The automated robotic inspection was implemented for all UT, EC, and CI sensors individually where a novel sensor-enabled robotic system based on a real-time embedded controller was developed. The system components consisting of a KUKA robotic arm, Force/Torque (F/T) sensor, and NDE sensor and controller were interfaced through a core program in LabVIEW enabling a) real-time communication between different hardware, b) data acquisition from all sensors and c) full control of the processes within the cell. Moreover, real-time robot motion corrections driven by the F/T sensor feedback were established to adjust the contact force and orientation of the sensors to the component surface during the scan. All sensors, including the UT roller-probe, EC array, and CI sensor boards, were robotically delivered on the designated surface notches with varying depths of 0.1, 0.2, 0.5, and 5 mm. The results of EC and CI testing showed enhanced detectability with high SNR for the defects shallower than 0.2 mm when compared to the UT B-scan images.