scholarly journals Inspection of Defects in CFRP based on Principal Components

2019 ◽  
Vol 8 (3) ◽  
pp. 2367-2370
Keyword(s):  
Thermal Wave ◽  
Principal Component ◽  
Destructive Testing ◽  
Excitation Scheme ◽  
Reinforced Plastic ◽  
Wave Imaging ◽  
Carbon Fibre Reinforced Plastic ◽  
Processing Techniques ◽  
Subsurface Defects ◽  
Thermal Wave Imaging

Recent advances in thermal non-destructive testing (TNDT) witnessed improved defect detection capabilities in various fields. Active thermography enables fast and easy inspection of products made of composites. A number of post processing techniques are being developed with an aim to enhance the subsurface defects from the thermographic data. This paper explores the idea of applying principal component analysis (PCA) to thermal wave imaging for possible enhancement of subsurface defects in carbon fibre reinforced plastic (CFRP) material. The experimentation is carried over CFRP sample using quadrature frequency modulated thermal wave imaging (QFMTWI) excitation scheme and results are compared with conventional phase based methods. The results demonstrate the potential of this approach for detecting subsurface defects in CFRP.

scholarly journals Defect Detection Based on Segmentation of Thermographic Images of Frequency Modulated Thermal Wave Imaging

2021 ◽  
Vol 10 (3) ◽  
pp. 210-214
Author(s):  
V.Phani Bhushan ◽  
K. Murali ◽  
K.S. Sagar Reddy
Keyword(s):  
Image Segmentation ◽  
Image Fusion ◽  
Thermal Wave ◽  
Destructive Testing ◽  
Segmented Images ◽  
Wave Imaging ◽  
Image Fusion Technique ◽  
Processing Techniques ◽  
Non Destructive ◽  
Thermal Wave Imaging

To improve the usefulness of the data, the raw images acquired during non-destructive testing should be processed by image processing techniques. In this paper, by Frequency Modulated Thermal Wave Imaging, we use the image fusion technique to boost the detection capability of defects in a GFRP sample with 25 squared Teflon inserts of different sizes positioned at various depths. In applications such as detection, image segmentation is useful where it is difficult to process the entire image at a time. In this paper, Adaptive Thresholding Image segmentation is used to classify the delamination in Thermographic Images of Infrared Non-Destructive Research on images captured at two different times. Image fusion is later applied to segmented images. Image fusion is used to merge two or more pictures of a different focus and to provide the best picture quality. Fusion is carried out using the Basic Averaging Method here. Using Relative Foreground Area error, the performance of the proposed method is quantitatively assessed. The region and shape of an object are important parameters in the case of Non-Destructive Evaluation. Such parameters are contrasted with current methods of segmentation

scholarly journals Numerical Simulation of Non-Destructive Characterization of CFRP Composite Through Frequency Modulated Thermal wave Imaging

2019 ◽  
Vol 8 (4) ◽  
pp. 9754-9757
Keyword(s):  
Numerical Simulation ◽  
Defect Detection ◽  
Thermal Wave ◽  
Pulse Compression ◽  
Principal Component ◽  
Random Projection ◽  
Area Of Interest ◽  
Wave Imaging ◽  
Non Destructive ◽  
Thermal Wave Imaging

Non-destructive testing plays a vital role in industrial and biomedical applications. Non-stationary stimulation based active Infrared thermography is an emerging area of interest in subsurface defect detection and visualization. In present article, frequency modulated thermal wave imaging is employed on a numerical simulation to detect defects of CFRP specimen and applied various post processing techniques such as FFT phase, Pulse compression, principal component analysis and random projection transform for better defect detection. Defect Signal to noise ratios considered as merit of analysis.

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