Surface representation of pulsed eddy current sensor signals for improved ferromagnetic material thickness quantification

Nalika Ulapane, Karthick Thiyagarajan, Jaime Miro, Sarath Kodagoda

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)

Abstract

Pulsed eddy current (PEC) sensing is a non-destructive testing and evaluation technique widely used for detecting and quantification of flaws and properties of metallic test pieces. In recent years, the use of the technique for the assessment of ferromagnetic materials, specifically, for the purpose of thickness quantification of ferromagnetic plates, or wall-like structures, has risen. The detector coil-based PEC sensor architecture has been the most commonly used sensor architecture for the purpose. Recent works have demonstrated the effectiveness of the detector coil voltage decay rate for this purpose. The decay rate signal feature has been used to construct a linear functional relationship between thickness and the feature value. This functional relationship has eventually been used for thickness estimation. However, this method has proven to come with a limitation of accuracy in thickness estimates. Therefore, we present in this article a method for surface representation of PEC sensor signals. In this method, the thickness varies as a surface-like function in 3D, relying on two signal feature values provided as independent variables. We demonstrate how the surface representation yields a 2% improvement in accuracy (with respect to correlation coefficient) in previous results (i.e., thickness estimates) through a case-study of quantifying wall thickness of a gray cast iron pipe. Such an improvement in accuracy has significant cost-saving implications in the field of structural health monitoring, especially in managing critical pipes in sectors such as water and energy. Cost savings result by enabling infrastructure managers to optimize rehabilitation and thereby provide improved services.
Original languageEnglish
Article number9244144
Pages (from-to)5413-5422
Number of pages10
JournalIEEE Sensors Journal
Volume21
Issue number4
DOIs
Publication statusPublished - 15 Feb 2021

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