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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
Quantifying impacts on remote photogrammetric inspection using unmanned aerial vehicles
Abstract
Remote photogrammetric inspection is a Non-Destructive Testing method used to quantify surface integrity and detect external discontinuities. The mobility and size of an unmanned aerial vehicle (UAV) offer the flexibility to quickly deploy remote photogrammetric inspections for large-scale assets. In this paper, the results of a photogrammetric inspection are presented as a 3D profile, reconstructed from UAV captured images. Experiments were conducted indoors using a wind turbine blade section obtained from a recently decommissioned asset. The naturally occurring surface features representative of environmental wear were augmented with a small number of artificial features to aid in the visualisation of inspection quality. An autonomous UAV system for photogrammetric inspections is demonstrated and the influence of image parameters such as environmental light levels, motion blur and focal blur quantified in terms of their impact on the inspection accuracy. Over the range of parameter values studied, the poorest scenario was observed to cause a degradation in reconstruction error by a factor of 13 versus the optimal. Reconstruction quality when employing a laser range scanner to maintain standoff distance relative to the object during flight was also investigated. In this schema, the controller automatically generated a real-time adaptive flight path to follow the outer profile of the wind turbine blade and, consequently, demonstrated improved image quality during close-range inspection of an object with complex geometry.Inspection accuracy was quantified using the error of the photogrammetric reconstruction as compared to a model acquired using independent metrology equipment. While utilising the laser-based adaptive path, error in the reconstructed geometry was reduced by a factor of 2.7 versus a precomputed circular path. In the best case, the mean deviation was below 0.25 mm. Instances of wind turbine blade damage such as edge crushing, surface imperfections, early stage leading edge erosion were clearly observed in the textured 3D reconstruction profiles, indicating the utility of the successful inspection process. The results of this paper evaluate the impact of optical environmental effects on photogrammetric inspection accuracy, offering practical insight towards mitigation of negative effects.