Specified value based defect depth prediction using pulsed thermography

2012 ◽  
Vol 112 (2) ◽  
pp. 023112 ◽  
Author(s):  
Zhi Zeng ◽  
Ning Tao ◽  
Lichun Feng ◽  
Cunlin Zhang
Keyword(s):  
Defect Depth ◽  
Pulsed Thermography ◽  
Depth Prediction

Analysis of Pulsed Thermography Methods for Defect Depth Prediction

2005 ◽  
Vol 128 (4) ◽  
pp. 329-338 ◽  
Author(s):  
J. G. Sun
Keyword(s):  
Test Specimen ◽  
Three Dimensional ◽  
Quantitative Prediction ◽  
Defect Depth ◽  
Effective Technique ◽  
Flat Bottom ◽  
Dimensional Solution ◽  
Pulsed Thermography ◽  
One Dimensional ◽  
Depth Prediction

Pulsed thermography is an effective technique for quantitative prediction of defect depth within a specimen. Several methods have been reported in the literature. In this paper, using an analysis based on a theoretical one-dimensional solution of pulsed thermography, we analyzed four representative methods. We show that all of the methods are accurate and converge to the theoretical solution under ideal conditions. Three methods can be directly used to predict defect depth. However, because defect features that appear on the surface during a pulsed thermography test are always affected by three-dimensional heat conduction within the test specimen, the performance and accuracy of these methods differs for defects of various sizes and depths. This difference is demonstrated and evaluated from a set of pulsed thermography data obtained from a specimen with several flat-bottom holes as simulated defects.

Defect Depth Quantification Using Pulsed Thermography

2012 ◽  
Vol 585 ◽  
pp. 72-76 ◽  
Author(s):  
D. Sharath ◽  
M. Menaka ◽  
B. Venkatraman
Keyword(s):  
Depth Estimation ◽  
Defect Size ◽  
Defect Depth ◽  
Pulsed Thermography ◽  
Full Field ◽  
First Derivative ◽  
Derivative Method ◽  
Aisi 316 ◽  
Materials Used ◽  
Defect Quantification

Pulsed Thermography is an advanced NDE technique which is becoming popular due to fast inspection rate, non contact nature and it gives full field image. Pulsed Thermography is successfully applied for defect detection, defect depth estimation, coating thickness evaluation and delamination detection in coatings but it is limited for evaluation of subsurface defects (of the order of few mm). In this paper we discuss the application of Pulsed Thermography for defect quantification and effect of defect size on it in AISI 316 grade SS which are important structural materials used in nuclear and other industries. Log First Derivative method is considered for defect depth quantification and the results are compared with Finite Difference Modeling carried out using ThermoCalc 6L software.

scholarly journals An Analytical Model for Defect Depth Estimation Using Pulsed Thermography

2016 ◽  
Vol 56 (6) ◽  
pp. 1111-1122 ◽  
Author(s):  
S.L. Angioni ◽  
F. Ciampa ◽  
F. Pinto ◽  
G. Scarselli ◽  
D.P. Almond ◽  
...  
Keyword(s):  
Analytical Model ◽  
Depth Estimation ◽  
Defect Depth ◽  
Pulsed Thermography

Effect of defect size on defect depth quantification in pulsed thermography

2013 ◽  
Vol 24 (12) ◽  
pp. 125205 ◽  
Author(s):  
D Sharath ◽  
M Menaka ◽  
B Venkatraman
Keyword(s):  
Defect Size ◽  
Defect Depth ◽  
Pulsed Thermography

scholarly journals Characterizing Depth of Defects with Low Size/Depth Aspect Ratio and Low Thermal Reflection by Using Pulsed IR Thermography

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 1886
Author(s):  
Alexey I. Moskovchenko ◽  
Michal Švantner ◽  
Vladimir P. Vavilov ◽  
Arsenii O. Chulkov
Keyword(s):  
Quantitative Estimation ◽  
Signal Reconstruction ◽  
Heat Diffusion ◽  
Defect Characterization ◽  
Ir Thermography ◽  
Defect Depth ◽  
Depth Prediction ◽  
Aspect Ratios ◽  
3D Printed ◽  
Novel Method

This study is focused on the quantitative estimation of defect depth by applying pulsed thermal nondestructive testing. The majority of known defect characterization techniques are based on 1D heat conduction solutions, thus being inappropriate for evaluating defects with low aspect ratios. A novel method for estimating defect depth is proposed by taking into account the phenomenon of 3D heat diffusion, finite lateral size of defects and the thermal reflection coefficient at the boundary between a host material and defects. The method is based on the combination of a known analytical model and a non-linear fitting (NLF) procedure. The algorithm was verified both numerically and experimentally on 3D-printed polylactic acid plastic samples. The accuracy of depth prediction using the proposed method was compared with the reference characterization technique based on thermographic signal reconstruction to demonstrate the efficiency of the proposed NLF method.

scholarly journals Defect Depth Estimation in Infrared Thermography with Deep Learning

2021 ◽  
Author(s):  
Qiang Fang ◽  
farima abdollahi-mamoudan ◽  
Xavier Maldague
Keyword(s):  
Infrared Thermography ◽  
Low Cost ◽  
Depth Estimation ◽  
Defect Depth ◽  
Fem Modeling ◽  
Flat Bottom ◽  
Pulsed Thermography ◽  
And Performance ◽  
Gated Recurrent Units ◽  
Non Destructive

Infrared thermography has already been proven to be a significant method in non-destructive evaluation since it gives information with immediacy, rapidity, and low cost. However, the thorniest issue for the wider application of IRT is quantification. In this work, we proposed a specific depth quantifying technique by employing the Gated Recurrent Units (GRU) in composite material samples via pulsed thermography (PT). Finite Element Method (FEM) modeling provides the economic examination of the response pulsed thermography. In this work, Carbon Fiber Reinforced Polymer (CFRP) specimens embedded with flat bottom holes are stimulated by a FEM modeling (COMSOL) with precisely controlled depth and geometrics of the defects. The GRU model automatically quantified the depth of defects presented in the stimulated CFRP material. The proposed method evaluated the accuracy and performance of synthetic CFRP data from FEM for defect depth predictions.

Depth prediction of non-air interface defect using pulsed thermography

2012 ◽  
Vol 48 ◽  
pp. 39-45 ◽  
Author(s):  
Zhi Zeng ◽  
Chunguang Li ◽  
Ning Tao ◽  
Lichun Feng ◽  
Cunlin Zhang
Keyword(s):  
Pulsed Thermography ◽  
Depth Prediction ◽  
Air Interface ◽  
Interface Defect
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