Modal-based vibrothermography using feature extraction with application to composite materials

Xintian Chi*, Dario Di Maio, Nicholas A.J. Lieven

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

Abstract

This research focuses on the development of a damage detection algorithm based on modal testing, vibrothermography, and feature extraction. The theoretical development of mathematical models is presented to illustrate the principles supporting the associated algorithms, through which the importance of the three components contributing to this approach is demonstrated. Experimental tests and analytical simulations have been performed in laboratory conditions to show that the proposed damage detection algorithm is able to detect, locate, and extract the features generated due to the presence of sub-surface damage in aerospace grade composite materials captured by an infrared camera. Through tests and analyses, the reliability and repeatability of this damage detection algorithm are verified. In the concluding observations of this article, suggestions are proposed for this algorithm’s practical applications in an operational environment.

Original languageEnglish
Pages (from-to)967-986
Number of pages20
JournalStructural health monitoring
Volume19
Issue number4
Early online date9 Sep 2019
DOIs
Publication statusPublished - 1 Jul 2020

Keywords

  • composite materials
  • damage detection
  • feature extraction
  • finite element analysis
  • independent component analysis
  • infrared thermography
  • modal testing
  • principal component analysis
  • Structural health monitoring
  • vibrothermography

Fingerprint Dive into the research topics of 'Modal-based vibrothermography using feature extraction with application to composite materials'. Together they form a unique fingerprint.

Cite this