Pipeline inspection using magnetic induction tomographybased on a narrowband pass filtering method

Lu Ma, Hsin-Yu Wei, Manuchehr Soleimani

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

Pipelines are the most common apparatus in industries; therefore, the need for inspection during the manufacturing, construction and the operation stage is inevitable and invaluable. Magnetic Induction Tomography (MIT) is a new type of tomography technique that is sensitive to the electrical conductivity of objects.~It has been shown that the MIT technique is appropriate for imaging materials with high electrical conductivity contrasts; hence, the majority of the MIT systems were designed for detecting metallic objects. In this paper, MIT technique was proposed for pipeline inspection. Structural damages of the outer surface of the pipe were considered in this study. Nonetheless, it is challenging to use the traditional MIT pixel based reconstruction method (PBRM) as a suitable pipelines inspection tool because of the limited resolution. A narrowband pass filtering method (NPFM) of imaging pipe geometry was developed as a suitable image reconstruction method.~The proposed method can overcome the resolution limitations and produce useful information of the pipe structure.~This paper shows the comparative results from the novel NPFM and from traditional PBRM. While the PBRM fails to detect damages in outer structure of the pipe the NPFM successfully indentifies these damages. The method has been verified using experimental data from very challenging test samples. It is well known that using a coil array with an imaging region of 100 mm the PBRM based MIT can retrieve information with accuracy of about 10 mm (about 10%). With proposed NPFM the information on a resolution of 2 mm (which is about 2%) can be detected using the same measurement data.
Original languageEnglish
Pages (from-to)65-78
Number of pages14
JournalProgress In Electromagnetics Research M
Volume23
Publication statusPublished - 2012

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