Classification, identification, and quantitative study of defects in aluminum plates using pulsed alternating current field measurement combined with principal component analysis

Introduction This study investigates an approach for defect characterization in non-ferromagnetic materials by combining Pulsed Alternating Current Field Measurement (PACFM) with Principal Component Analysis (PCA). The research demonstrates how this integrated method can effectively classify and quantify both surface and subsurface defects through signal processing of PACFM data. Methods The PACFM technique was utilized to acquire defect response signals from non-ferromagnetic specimens. Subsequently, PCA was implemented to decompose the multidimensional PACFM datasets into principal components, with each component preserving the most diagnostically significant information. In this analytical framework, the classification of defects was determined by the sign of the mapped value w 2 in the PCA eigenvector direction, while the magnitude of w 2 exhibited a correlation with subsurface defect burial depths. Results The integrated PACFM-PCA approach successfully discriminated between surface and subsurface defects. The polarity of the principal component w 2 served as a reliable feature for defect classification, with positive values consistently corresponding to subsurface defects and negative values indicating surface defects. Furthermore, a robust quadratic relationship correlation was established between the eigenspace coordinates of subsurface defect signals and their respective burial depths, enabling accurate quantitative assessment of burial depth. Discussion The integration of PACFM with PCA provides a robust framework for defect analysis in non-ferromagnetic materials. This synergistic approach demonstrates significant capability in extracting and quantifying defect signatures from complex response signals, highlighting its considerable potential for non-destructive testing (NDT) applications. Future work could explore its adaptability to more intricate defect geometries.

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Publication Details

Journal
Frontiers in Materials
Published
2025-04-14
DOI
https://doi.org/10.3389/fmats.2025.1569055
Primary Topic
Non-Destructive Testing Techniques
Type
article
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article

Classification, identification, and quantitative study of defects in aluminum plates using pulsed alternating current field measurement combined with principal component analysis

Xinfeng Li, Shaoming Pan, Qingxiao Kong, Li-Zhi Lin
Frontiers in Materials
Non-Destructive Testing Techniques
article

Classification, identification, and quantitative study of defects in aluminum plates using pulsed alternating current field measurement combined with principal component analysis

Xinfeng Li, Shaoming Pan, Qingxiao Kong, Li-Zhi Lin
article en

Abstract

Introduction This study investigates an approach for defect characterization in non-ferromagnetic materials by combining Pulsed Alternating Current Field Measurement (PACFM) with Principal Component Analysis (PCA). The research demonstrates how this integrated method can effectively classify and quantify both surface and subsurface defects through signal processing of PACFM data. Methods The PACFM technique was utilized to acquire defect response signals from non-ferromagnetic specimens. Subsequently, PCA was implemented to decompose the multidimensional PACFM datasets into principal components, with each component preserving the most diagnostically significant information. In this analytical framework, the classification of defects was determined by the sign of the mapped value w 2 in the PCA eigenvector direction, while the magnitude of w 2 exhibited a correlation with subsurface defect burial depths. Results The integrated PACFM-PCA approach successfully discriminated between surface and subsurface defects. The polarity of the principal component w 2 served as a reliable feature for defect classification, with positive values consistently corresponding to subsurface defects and negative values indicating surface defects. Furthermore, a robust quadratic relationship correlation was established between the eigenspace coordinates of subsurface defect signals and their respective burial depths, enabling accurate quantitative assessment of burial depth. Discussion The integration of PACFM with PCA provides a robust framework for defect analysis in non-ferromagnetic materials. This synergistic approach demonstrates significant capability in extracting and quantifying defect signatures from complex response signals, highlighting its considerable potential for non-destructive testing (NDT) applications. Future work could explore its adaptability to more intricate defect geometries.

Frontiers in MaterialsVol. 12
Wenzhou University (CN), Wenzhou Polytechnic (CN)
Openalex Percentile: Top 93%
Non-Destructive Testing Techniques
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