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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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Zhang, Jie
University of Bristol
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (7/7 displayed)
- 2022Sizing limitations of ultrasonic array images for non-sharp defects and their impact on structural integrity assessmentscitations
- 2020Data fusion of multi-view ultrasonic imaging for characterisation of large defectscitations
- 2020Effect of crack-like defects on the fracture behaviour of Wire + Arc additively manufactured nickel-base Alloy 718citations
- 2012Monte Carlo inversion of ultrasonic array data to map anisotropic weld propertiescitations
- 2012Autofocus imaging
- 2010Ultrasonic condition monitoring using thin-film piezoelectric sensorscitations
- 2006Monitoring of lubricant film failure in a ball bearing using ultrasoundcitations
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document
Autofocus imaging
Abstract
<p>The quality of an ultrasonic array image, especially for anisotropic material, depends on accurate information about acoustic properties. Inaccuracy of acoustic properties causes image degradation, e.g., blurring, errors in locating of reflectors and introduction of artifacts. In this paper, for an anisotropic austenitic steel weld, an autofocus imaging technique is presented. The array data from a series of beacons is captured and then used to statistically extract anisotropic weld properties by using a Monte-Carlo inversion approach. The beacon and imaging systems are realized using two separated arrays; one acts as a series of beacons and the other images these beacons. Key to the Monte-Carlo inversion scheme is a fast forward model of wave propagation in the anisotropic weld and this is based on the Dijkstra algorithm. Using this autofocus approach a measured weld map was extracted from an austenitic weld and used to reduce location errors, initially greater than 6mm, to less than 1mm. © 2012 American Institute of Physics.</p>