Characteristic of Pulsed Eddy Current Signal Pattern to Detect Wall Thinning of Carbon Steel Tube

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Park, D.
Kishore, M.
Lee, D.
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Review of Progress in Quantitative Nondestructive Evaluation
Center for Nondestructive Evaluation

Begun in 1973, the Review of Progress in Quantitative Nondestructive Evaluation (QNDE) is the premier international NDE meeting designed to provide an interface between research and early engineering through the presentation of current ideas and results focused on facilitating a rapid transfer to engineering development.

This site provides free, public access to papers presented at the annual QNDE conference between 1983 and 1999, and abstracts for papers presented at the conference since 2001.


The pipelines used under high pressure and high temperatures in nuclear power plants, oil and gas, petrochemical and other energy related industries are made of ferromagnetic carbon steel. In order to increase the efficiency, the pipelines are always covered with low conductive thermal insulators to refrain from thermal emission and absorption and externally protected by cladding sheets made of aluminum alloy, stainless steel or galvanized steel. Non Destructive Technique (NDT) methods that are capable of detecting the wall thinning and defects without removing the insulation are necessary [1]. In this study we developed a Pulsed Eddy Current (PEC) system to detect wall thinning of Ferro magnetic steel pipes. The developed system is capable of decimating the thickness change of pipe line through 95mm fiber glass thermal insulator and 0.4mmAluminum (Al) cladding. A differential type PEC probe using Hall sensors was fabricated for this experiment; Peak amplitude and time to peak of the PEC signals obtained from various thickness regions of the test sample were analyzed in time domain. Results show a very good change corresponding to the sample thickness. In addition to time domain analysis, wavelet based signal processing technique was applied, in specific wavelet packet analysis based algorithm that utilizes the encoding technique was developed in MATLAB platform. Results were visualized and are found to be in good agreement with the time domain analysis.