Extension of the thermographic signal reconstruction technique for an automated segmentation and depth estimation of subsurface defects

Alexander Schager, Gerald Zauner, Günther Mayr, Peter Burgholzer

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

With increased use of light-weight materials with low factors of safety, non-destructive testing becomes increasingly important. Thanks to the advancement of infrared camera technology, pulse thermography is a cost efficient way to detect subsurface defects non-destructively. However, currently available evaluation algorithms have either a high computational cost or show poor performance if any geometry other than the most simple kind is surveyed. We present an extension of the thermographic signal reconstruction technique which can automatically segment and image defects from sound areas, while also estimating the defect depth, all with low computational cost. We verified our algorithm using real world measurements and compare our results to standard active thermography algorithms with similar computational complexity. We found that our algorithm can detect defects more accurately, especially when more complex geometries are examined.

Original languageEnglish
Article number96
JournalJournal of Imaging
Volume6
Issue number9
DOIs
Publication statusPublished - Sep 2020

Keywords

  • Active thermography
  • Automatic defect segmentation
  • Composite material
  • Defect imaging
  • Depth estimation
  • Pulse thermography
  • Thermographic signal reconstruction

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