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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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Dobie, Gordon
University of Strathclyde
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (21/21 displayed)
- 2024CNN-based automated approach to crack-feature detection in steam cycle componentscitations
- 2023Flexible and automated robotic multi-pass arc welding
- 2023Application of machine learning techniques for defect detection, localisation, and sizing in ultrasonic testing of carbon fibre reinforced polymers
- 2023Mapping SEARCH capabilities to Spirit AeroSystems NDE and automation demand for composites
- 2023Tactile, orientation, and optical sensor fusion for tactile breast image mosaickingcitations
- 2023Driving towards flexible and automated robotic multi-pass arc welding
- 2022Automated bounding box annotation for NDT ultrasound defect detection
- 2022Multi-sensor electromagnetic inspection feasibility for aerospace composites surface defects
- 2021A cost-function driven adaptive welding framework for multi-pass robotic weldingcitations
- 2021Non-contact in-process ultrasonic screening of thin fusion welded jointscitations
- 2021Miniaturised SH EMATs for fast robotic screening of wall thinning in steel platescitations
- 2020Quantifying impacts on remote photogrammetric inspection using unmanned aerial vehiclescitations
- 2019Electromagnetic acoustic transducers for guided-wave based robotic inspection
- 2019Towards guided wave robotic NDT inspection
- 2018Machining-based coverage path planning for automated structural inspectioncitations
- 2017Assessment of corrosion under insulation and engineered temporary wraps using pulsed eddy-current techniques
- 2017An expert-systems approach to automatically determining flaw depth within candu pressure tubes
- 2016Robotic ultrasonic testing of AGR fuel claddingcitations
- 2016Conformable eddy current array deliverycitations
- 2014Automatic ultrasonic robotic arraycitations
- 2013The feasibility of synthetic aperture guided wave imaging to a mobile sensor platformcitations
Places of action
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article
A cost-function driven adaptive welding framework for multi-pass robotic welding
Abstract
Manual teaching of robot paths and welding parameters for multi-pass robotic welding is a cumbersome and time-consuming task, which decreases the flexibility, adaptability, and potential of such systems. This paper introduces and presents a new automated weld parameter and pass deposition sequencing framework, which builds on the current state of the art developments and enables automatic planning of multi-pass welding for single-sided V-groove geometries. By integrating a novel cost-function concept that permutates and identifies the welding parameters for each layer through a user-driven weighting, the framework delivers the minimum number of passes, filler material and welding arc time based on application requirements. A mathematical model relating the cross-section area of beads with the pose of the torch and weaving width was built upon to allow full-process automated welding parameter generation and adaption for different geometric characteristics of the groove. The concept methodology and framework were then developed and verified experimentally, through robotically deployed Metal Active Gas (MAG) welding. For a given representative joint, the arc welding time and amount of filler wire were found to be 32.9 % and 26.18 % lower respectively, than the worst-case available welding parameter combination, delivering a corresponding decrease in direct automated welding manufacturing costs. Lastly, an ultrasonic inspection was undertaken to verify the consistent quality of the weldments validating the framework outcome and enabling welding pass automation through robotic systems.