Early results for equivalent wavefield transform as a direct solution to the inverse problem for active infrared thermography and potential for perfusion information to differentiate healthy versus cancerous breast tissue

2020 ◽  
Author(s):  
Jonathan P. Gershenson ◽  
Meir Gershenson
Keyword(s):  
Inverse Problem ◽  
Infrared Thermography ◽  
Breast Tissue ◽  
Direct Solution ◽  
Active Infrared Thermography ◽  
Early Results

scholarly journals A Method of Defect Depth Recognition in Active Infrared Thermography Based on GRU Networks

2021 ◽  
Vol 11 (14) ◽  
pp. 6387
Author(s):  
Li Xu ◽  
Jianzhong Hu
Keyword(s):  
Infrared Thermography ◽  
Visual Information ◽  
Evaluation Method ◽  
Recognition Performance ◽  
Principal Component ◽  
Defect Depth ◽  
Model Learning ◽  
Flat Bottom ◽  
Bp Network ◽  
Active Infrared Thermography

Active infrared thermography (AIRT) is a significant defect detection and evaluation method in the field of non-destructive testing, on account of the fact that it promptly provides visual information and that the results could be used for quantitative research of defects. At present, the quantitative evaluation of defects is an urgent problem to be solved in this field. In this work, a defect depth recognition method based on gated recurrent unit (GRU) networks is proposed to solve the problem of insufficient accuracy in defect depth recognition. AIRT is applied to obtain the raw thermal sequences of the surface temperature field distribution of the defect specimen. Before training the GRU model, principal component analysis (PCA) is used to reduce the dimension and to eliminate the correlation of the raw datasets. Then, the GRU model is employed to automatically recognize the depth of the defect. The defect depth recognition performance of the proposed method is evaluated through an experiment on polymethyl methacrylate (PMMA) with flat bottom holes. The results indicate that the PCA-processed datasets outperform the raw temperature datasets in model learning when assessing defect depth characteristics. A comparison with the BP network shows that the proposed method has better performance in defect depth recognition.

Damage Assessment of Helicoidal CFRP Using Active Infrared Thermography

2021 ◽  
pp. 97-100
Author(s):  
Jonathan Zheng ◽  
Carlos Manzano ◽  
Vinod Kumar ◽  
Andrew Ngo
Keyword(s):  
Infrared Thermography ◽  
Damage Assessment ◽  
Active Infrared Thermography
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