An infrared-induced terahertz imaging modality for foreign object detection in a lightweight honeycomb composite structure

Hai Zhang, Stefano Sfarra, Ahmad Osman, Klaus Szielasko, Christopher Stumm, Marc Genest, Xavier P.V. Maldague

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

In this paper, terahertz time-domain spectroscopy (THz-TDS) is used for the first time to detect fabricated defects in a glass fiber-skinned lightweight honeycomb composite panel. A novel amplitude polynomial regression (APR) algorithm is proposed as a preprocessing method. This method segments the amplitude-frequency curves to simulate the heating and the cooling monotonic behavior as in infrared thermography. Then, the method of empirical orthogonal function (EOF) imaging is applied on the APR preprocessed data as a postprocessing algorithm. Signal-to-noise ratio analysis is performed to verify the image improvement of the proposed APR-EOF modality from a quantitative point of view. Finally, the experimental results and the physical analysis show that THz is more suitable with respect to the detection of defects in glass fiber lightweight honeycomb composites.

Original languageEnglish
Article number8353417
Pages (from-to)5629-5636
Number of pages8
JournalIEEE Transactions on Industrial Informatics
Volume14
Issue number12
DOIs
Publication statusPublished - 1 Dec 2018

Keywords

  • Empirical orthogonal function (EOF)
  • fourier transform
  • lightweight honeycomb
  • polynomial fitting
  • terahertz (THz)

ASJC Scopus subject areas

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

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