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Open AccessArticle

Extension of the Thermographic Signal Reconstruction Technique for an Automated Segmentation and Depth Estimation of Subsurface Defects

1
Josef Ressel Centre for Thermal NDE of Composites, University of Applied Sciences Upper Austria, 4600 Wels, Austria
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RECENDT—Research Centre for Nondestructive Testing, 4040 Linz, Austria
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Author to whom correspondence should be addressed.
J. Imaging 2020, 6(9), 96; https://doi.org/10.3390/jimaging6090096
Received: 30 July 2020 / Revised: 7 September 2020 / Accepted: 8 September 2020 / Published: 11 September 2020
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. View Full-Text
Keywords: active thermography; pulse thermography; thermographic signal reconstruction; depth estimation; automatic defect segmentation; defect imaging; composite material active thermography; pulse thermography; thermographic signal reconstruction; depth estimation; automatic defect segmentation; defect imaging; composite material
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Schager, A.; Zauner, G.; Mayr, G.; Burgholzer, P. Extension of the Thermographic Signal Reconstruction Technique for an Automated Segmentation and Depth Estimation of Subsurface Defects. J. Imaging 2020, 6, 96.

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