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Article . 2022 . Peer-reviewed
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Analyzing probability of detection as a function of defect size and depth in pulsed IR thermography

Authors: Alexey Moskovchenko; Michal Švantner; Vladimir Vavilov; Arsenii Chulkov;

Analyzing probability of detection as a function of defect size and depth in pulsed IR thermography

Abstract

This study introduces a novel approach to the presentation of the probability of detection (POD) function in infrared (IR) thermographic nondestructive testing. The modified POD is suggested as a function of two defect parameters, namely, defect depth and lateral size. The proposed approach is based on calculating theoretical values of maximum temperature contrast for many defect size/depth combinations by using an appropriate analytical model. Furthermore, these values are used for the quantification of defects to produce predicted POD curves by applying a signal/response method. The results appear as the POD maps illustrating detectability of defects with various size/depth combinations. By setting a particular POD threshold, for example, 90%, the detectability limit contours can be obtained. These contours illustrate the limiting combinations of the depth and diameter of the defects, which can be detected with a required probability of correct detection under a particular temperature signal threshold. The proposed methodology is illustrated with an example of using the POD approach in pulsed IR thermographic inspection of a 3D printed specimen with artificial sphere-like defects. Such an approach allows predicting the detectability of defects in a vast range of depth/size ratios by using an analytical model and a limited number of experiments.

Keywords

Detectability, инфракрасная термография, Infrared thermography, глубина дефекта, Probability of detection, вероятность обнаружения, Defect depth

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
Top 10%
Top 10%
Top 10%
Green