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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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Maldague, Xavier
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Publications (5/5 displayed)
- 2023Fusion insights from ultrasonic and thermographic inspections for impact damage analysiscitations
- 2023Defect Detection and Depth Estimation in Composite Materials for Pulsed Thermography Images by Nonuniform Heating Correction and Oriented Gradient Information
- 2022Passive multivariate thermography on the mitigation of corrosion under insulation
- 2014Square Heating Applied to Shearography and Active Infrared Thermography Measurements Coupling: From Feasibility Test in Laboratory to Numerical Study of Pultruded CFRP Plates Glued on Concrete Specimencitations
- 2013Comparison between optical pulsed thermography and vibrothermography for the assessment of carbon fibers composite materials
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document
Passive multivariate thermography on the mitigation of corrosion under insulation
Abstract
<jats:p>Corrosion under insulation (CUI) is one of the major concerns of oil and petrochemical installations as damageevolves invisibly under insulation layers and usually revealed on the occurrence of leaking or more catastrophic failure. Methods to early detect CUI and its causes is an urgent necessity to assure safety and performance of insulated processpiping. Oil and petrochemical plants are often considered explosive environments in which thermal excitation devices areforbidden. The present work aims then on the consolidation of a passive thermographic methodology to reliably detectmoisture trapped under insulation layers that will cause corrosion. The proposed methodology focuses on the thermal behaviour of the piping structure during process variationsand interactions with the external ambient. The partial least-squares analysis showed promising performance on separatingdifferent physical phenomena and creating cleaner images for defect detection.</jats:p>