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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
In-process non-destructive evaluation of wire + arc additive manufacture components using ultrasound high-temperature dry-coupled roller-probe
Abstract
In 2019, the global metal Additive Manufacturing (AM) market size was valued at € 2.02 billion and was predicted to grow by up to 27.9% annually until 2024. Additive Manufacturing plays a significant role in Industry 4.0, where the demand for smart factories capable of fabricating high-quality customized products cost-efficiently exists. Wire + Arc Additive Manufacturing (WAAM) is one such technique that WAAM utilizes industrial robotics and arc-based welding processes to produce components on a layer-by-layer basis. is enables automated, time and material-efficient production of high-value and geometrically complex metal parts. To strengthen the benefits, the demand for robotically deployed in-process Non-Destructive Evaluation (NDE) has risen, aiming to replace manually deployed inspection techniques deployed after the full part completion. <br/>The research presents a new synchronized multi-robot WAAM deposition & ultrasound NDE cell aiming to achieve defect detection in-process, enable possible in-process repair, and prevent costly scrappage or rework. Within the cell, the plasma-arc WAAM process, controlled by deposition software, is employed to build components. The full external control NDE approach is achieved by the real-time force/torque sensor-enabled adaptive kinematics control package. A high-temperature dry-coupled ultrasound roller-probe device is employed to assess the structural integrity of freshly deposited layers of WAAM components. The WAAM roller-probe is tailored to facilitate the in-process inspection by dry-coupling coupling with the hot (< 350 °C) non-flat surface of WAAM using a flexible outer silicone tyre and solid core delay-line at speed and at coupling high force[1-3].<br/>The demonstration of the in-process inspection approach is performed on hot as-built titanium (Ti-6Al-4V) WAAM samples. The defect detection capabilities are assessed on artificial tungsten reflectors embedded in WAAM builds. In this work the defect detection is accomplished and analyzed using two separate approaches 1) layer-specific beamforming focusing imaging and 2) volumetric inspection using post-processing algorithms applied on collected Full Matric Capture data. The ultrasound in-process inspection using the dry-coupled roller-probe is driven by live Ultrasound Testing (UT) data acquisition, initiated within a minute from layer deposition completion. The collected UT B-scan frames are based on electronically focused beamforming through the roller-probe media into the depth of targeted layers.Subsequently, the results are presented on a plotted C-scan image, showing a top view over the interior of the targeted built volume. The results in this work are analyzed and compared to the X-ray computed tomography scan, conducted after the full-built completion and sample processing. The processed UT images show positionally accurate detection of embedded tungsten reflectors, with a minimum of 15 dB of signal-to-noise ratio. An accurate size estimation is also achieved for the tungsten defect extended along the sample’s length. <br/>The outcome of this research shows a successful defect detection and hence directly supports the industrial benefits of the WAAM process intending to achieve the automated production of first-time-right parts.<br/>