Sparse Principal Component Thermography for Subsurface Defect Detection in Composite Products / Wu Jin-Yi , S. Sfarra, Yao Yuan
Уровень набора: IEEE Transactions on Industrial InformaticsЯзык: английский.Страна: .Резюме или реферат: Active thermography is an efficient and powerful technique for nondestructive testing of products made of composite materials, which enables rapid inspection of large areas, presents results as easily interpreted high-resolution images, and is easy to operate. In recent years, a number of thermographic data analysis methods were developed to enhance the visibility of subsurface defects, among which principal component thermography (PCT) is recommended because of its capability to enhance the contrast between defective and defect-free areas, compress data, and reduce noise. In this study, a sparse principal component thermography (SPCT) method is proposed, which inherits the advantages of PCT and allows more flexibility by introducing a penalization term. Compared to PCT, SPCT provides more interpretable analysis results owing to its structure sparsity. The feasibility and effectiveness of the proposed method are illustrated by the experimental results of the subsurface defect characterization in a carbon fiber reinforced plastic specimen..Примечания о наличии в документе библиографии/указателя: [References: 28 tit.].Аудитория: .Тематика: труды учёных ТПУ | электронный ресурс | active thermography | data analysis | nondestructive testing (NDT) | sparse principal component analysis (SPCA) | thermographic analysis | термография | неразрушающий контроль | термографический анализ Ресурсы он-лайн:Щелкните здесь для доступа в онлайнTitle screen
[References: 28 tit.]
Active thermography is an efficient and powerful technique for nondestructive testing of products made of composite materials, which enables rapid inspection of large areas, presents results as easily interpreted high-resolution images, and is easy to operate. In recent years, a number of thermographic data analysis methods were developed to enhance the visibility of subsurface defects, among which principal component thermography (PCT) is recommended because of its capability to enhance the contrast between defective and defect-free areas, compress data, and reduce noise. In this study, a sparse principal component thermography (SPCT) method is proposed, which inherits the advantages of PCT and allows more flexibility by introducing a penalization term. Compared to PCT, SPCT provides more interpretable analysis results owing to its structure sparsity. The feasibility and effectiveness of the proposed method are illustrated by the experimental results of the subsurface defect characterization in a carbon fiber reinforced plastic specimen.
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