Sparse principal component thermography for subsurface defect detection in composite products

Jin Yi Wu, Stefano Sfarra, Yuan Yao

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number8320318
Pages (from-to)5594-5600
Number of pages7
JournalIEEE Transactions on Industrial Informatics
Volume14
Issue number12
DOIs
Publication statusPublished - 1 Dec 2018

Fingerprint

Defects
Composite materials
Carbon fiber reinforced plastics
Image resolution
Nondestructive examination
Visibility
Inspection
Defect detection

Keywords

  • Active thermography
  • data analysis
  • nondestructive testing (NDT)
  • sparse principal component analysis (SPCA)
  • thermographic analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Sparse principal component thermography for subsurface defect detection in composite products. / Wu, Jin Yi; Sfarra, Stefano; Yao, Yuan.

In: IEEE Transactions on Industrial Informatics, Vol. 14, No. 12, 8320318, 01.12.2018, p. 5594-5600.

Research output: Contribution to journalArticle

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