This article summarizes the main results of an investigation about the corrosion detection in pipelines by infrared thermography, a non-destructive testing and evaluation technique that allows a reliable and fast analysis of large surfaces. The experimental work has been carried out in laboratory on a specimen that has been manufactured using a piece of a real pipeline system for oil transportation. Defects of different kinds have been artificially introduced in such a system to be tested by thermography. The objective is the detection and analysis of the presence of water in the pipeline jacketing system, that is the cause of the corrosion under insulation. Standards indicate thermography as a technique for the detection of this last phenomena, even though a precise procedure is not defined up today. This work aims at contributing in the specification of such a procedure.
Corrosion Detection in Pipelines Using Infrared Thermography: Experiments and Data Processing Methods
Cadelano G;Bortolin A;Ferrarini G;Bison P
2016
Abstract
This article summarizes the main results of an investigation about the corrosion detection in pipelines by infrared thermography, a non-destructive testing and evaluation technique that allows a reliable and fast analysis of large surfaces. The experimental work has been carried out in laboratory on a specimen that has been manufactured using a piece of a real pipeline system for oil transportation. Defects of different kinds have been artificially introduced in such a system to be tested by thermography. The objective is the detection and analysis of the presence of water in the pipeline jacketing system, that is the cause of the corrosion under insulation. Standards indicate thermography as a technique for the detection of this last phenomena, even though a precise procedure is not defined up today. This work aims at contributing in the specification of such a procedure.| File | Dimensione | Formato | |
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Descrizione: Corrosion Detection in Pipelines Using Infrared Thermography: Experiments and Data Processing Methods
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Descrizione: This is the accepted version of the article published in https://doi.org/10.1007/s10921-016-0365-5. © Springer Science+Business Media New York 2016
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