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Principal Component Analysis of Pulsed Eddy Current Response from Corrosion in Mild Steel

Lookup NU author(s): Mohammed Alamin, Professor Gui Yun TianORCiD


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The effect of corrosion under coatings on carbon steel is a complex mix of many factors, including electrical conductivity, magnetic permeability, surface roughness, and coating thickness variations, which all have to be taken into account when analysing the pulsed eddy current (PEC) response from corrosion. In this paper, the PEC nondestructive evaluation method has been applied to a set of mild steel plates with varying levels of corrosion and various surface preparations. The panels are exposed outdoors for the same time-period and then the surfaces prepared in different ways, resulting in four different corrosion grades in accordance with the surface preparation standards of the society for protective coatings. Using principal component analysis (PCA) on nonnormalized and normalized PEC response waveforms, the most dominant features are extracted and used to classify and characterize the samples. Normalization has been done in an attempt to mitigate the effects of magnetic permeability and lift-off variations across the samples. The distribution of the first principal component coefficients are then compared against other time-domain features of the PEC waveform to provide a physical explanation, and relate the changes to differences in the corrosion grade and other properties of the samples. Despite the complex nature of the samples, the results show that with the application of normalization and PCA, it is able to classify the samples into different corrosion grades.

Publication metadata

Author(s): Alamin M, Tian GY, Andrews A, Jackson P

Publication type: Article

Publication status: Published

Journal: IEEE Sensors Journal

Year: 2012

Volume: 12

Issue: 8

Pages: 2548-2553

Print publication date: 06/06/2012

ISSN (print): 1530-437X

ISSN (electronic): 1558-1748

Publisher: Institute of Electrical and Electronics Engineers


DOI: 10.1109/JSEN.2012.2195308


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