Physical insights into principal component thermography

2020 ◽  
Vol 62 (5) ◽  
pp. 277-280 ◽  
Author(s):  
K Kaur ◽  
A Sharma ◽  
A Rani ◽  
V Kher ◽  
R Mulaveesala

Among widely used non-destructive testing (NDT) methods, infrared thermography (IRT) has gained importance due to its fast, whole-field, remote and quantitative inspection capabilities for the evaluation of various materials. Being fast and easy to implement, pulsed thermography (PT) plays a vital role in the infrared thermographic community. This paper provides a physical insight into the selection of empirical orthogonal functions obtained from principal component pulsed thermography for the detection of subsurface defects located inside a mild steel specimen.

2015 ◽  
Vol 742 ◽  
pp. 128-131 ◽  
Author(s):  
Jian Min Zhou ◽  
Jun Yang ◽  
Qi Wan

This paper introduces the theory of eddy current pulsed thermography and expounds the research status of eddy current pulsed thermography in application and information extraction. Thermographic signal reconstruction, pulsed phase thermography, principal component analysis were introuduced in this paper and listed some fusion multiple methods to acquire information from infrared image. At last, it summarizes research progress, existing problem and deelopment of eddy current pulsed thermography.


Metals ◽  
2018 ◽  
Vol 8 (8) ◽  
pp. 612 ◽  
Author(s):  
Jue Hu ◽  
Weiping Xu ◽  
Bin Gao ◽  
Gui Tian ◽  
Yizhe Wang ◽  
...  

Eddy Current Pulsed Thermography is a crucial non-destructive testing technology which has a rapidly increasing range of applications for crack detection on metals. Although the unsupervised learning method has been widely adopted in thermal sequences processing, the research on supervised learning in crack detection remains unexplored. In this paper, we propose an end-to-end pattern, deep region learning structure to achieve precise crack detection and localization. The proposed structure integrates both time and spatial pattern mining for crack information with a deep region convolution neural network. Experiments on both artificial and natural cracks have shown attractive performance and verified the efficacy of the proposed structure.


Proceedings ◽  
2019 ◽  
Vol 27 (1) ◽  
pp. 13 ◽  
Author(s):  
Yousefi ◽  
Ibarra-Castanedo ◽  
Maldague

Detection of subsurface defects is undeniably a growing subfield of infrared non-destructive testing (IR-NDT). There are many algorithms used for this purpose, where non-negative matrix factorization (NMF) is considered to be an interesting alternative to principal component analysis (PCA) by having no negative basis in matrix decomposition. Here, an application of Semi non-negative matrix factorization (Semi-NMF) in IR-NDT is presented to determine the subsurface defects of an Aluminum plate specimen through active thermographic method. To benchmark, the defect detection accuracy and computational load of the Semi-NMF approach is compared to state-of-the-art thermography processing approaches such as: principal component thermography (PCT), Candid Covariance-Free Incremental Principal Component Thermography (CCIPCT), Sparse PCT, Sparse NMF and standard NMF with gradient descend (GD) and non-negative least square (NNLS). The results show 86% accuracy for 27.5s computational time for SemiNMF, which conclusively indicate the promising performance of the approach in the field of IR-NDT.


2021 ◽  
Vol 2021 (4) ◽  
pp. 70-82
Author(s):  
V.S. Eremenko ◽  
◽  
V.P. Babak ◽  
A.O. Zaporozhets ◽  
◽  
...  

The article describes the approach to the formation of a simulation model of information signals, which are typical for objects with different types of defects. The dispersive analysis of the signal spectrum components in the bases of the discrete Hartley transform and the discrete cosine transform is carried out. The analysis of the form of the reconstructed information signal is carried out depending on the number of coefficients of the spectral alignment in Hartley bases and cosine functions. The basis of orthogonal functions of a discrete argument is obtained, which can be used for the spectral transformation of information signals of a flaw detector. A method of simulation of information signals has been developed and experimentally investigated, which allows taking into account the deterministic and random components of the characteristics of real information signals. References 24, figures 13, tables 3.


2021 ◽  
Vol 11 (24) ◽  
pp. 12168
Author(s):  
Yoonjae Chung ◽  
Seungju Lee ◽  
Wontae Kim

Non-destructive testing (NDT) is a broad group of testing and analysis techniques used in science and industry to evaluate the properties of a material, structure, or system for characteristic defects and discontinuities without causing damage. Recently, infrared thermography is one of the most promising technologies as it can inspect a large area quickly using a non-contact and non-destructive method. Moreover, thermography testing has proved to be a valuable approach for non-destructive testing and evaluation of structural stability of materials. Pulsed thermography is one of the active thermography technologies that utilizes external energy heating. However, due to the non-uniform heating, lateral heat diffusion, environmental noise, and limited parameters of the thermal imaging system, there are some difficulties in detecting and characterizing defects. In order to improve this limitation, various signal processing techniques have been developed through many previous studies. This review presents the latest advances and exhaustive summary of representative signal processing techniques used in pulsed thermography according to physical principles and thermal excitation sources. First, the basic concept of infrared thermography non-destructive testing is introduced. Next, the principle of conventional pulsed thermography and signal processing technologies for non-destructive testing are reviewed. Then, we review advances and recent advances in each signal processing. Finally, the latest research trends are reviewed.


Author(s):  
Ling Miao ◽  
Bin Gao ◽  
Haoran Li ◽  
Guiyun Tian

Eddy current pulsed thermography (ECPT) has been widely used in the field of non-destructive testing due to its safety, non-contact detection, high spatial resolution and intuitive results. Inductive excitation source is an important component of ECPT and provides high-frequency alternating current to drive the excitation coil. However, a resonant frequency distortion phenomenon exists in the excitation source during the detection process, which seriously affects the output power of the excitation source and the sample detection effect. This paper presents a fast resonant frequency tracking loop for full bridge series resonant inverter which is used to search the resonance frequency in real time through direct digital synthesizer (DDS) and all-digital phase-locked loop. Theoretical analysis and simulation are presented to explain the working principle of the loop. Then, an experimental prototype is manufactured which serves as an excitation source for the ECPT experimental system. Compared with traditional excitation sources, the prototype does not need a water-cooled device and the tracking speed can be adjusted by modifying the parameters of DDS. Finally, experiments have been conducted on both artificial slot of 45# steel and natural cracks of rail and stainless steel to investigate the influence of resonant frequency tracking speed on the crack detection. The results revealed that reducing the resonant frequency tracking time can efficiently improve defect detectability and the manufactured prototype showed more application potential. This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.


Materials ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 3931
Author(s):  
Young-Geun Yoon ◽  
Jae-Yun Lee ◽  
Hajin Choi ◽  
Tae-Keun Oh

Prestressed concrete (PSC) is widely used for the construction of bridges. The collapse of several bridges with PSC has been reported, and insufficient grout and tendon corrosion were found inside the ducts of these bridges. Therefore, non-destructive testing (NDT) technology is important for identifying defects inside ducts in PSC structures. Electromagnetic (EM) waves have limited detection of internal defects in ducts due to strong reflections from the surface of the steel ducts. Spectral analysis of the existing impact echo (IE) method is limited to specific conditions. Moreover, the flexural mode in upper defects of ducts located at a shallow depth and delamination defects inside ducts are not considered. In this study, the applicability of the elastic wave of IE was analyzed, and multichannel analysis of surface, EM, and shear waves was employed to evaluate six types of PSC structures. A procedure using EM waves, IE, and principal component analysis (PCA) was proposed for a more accurate classification of defect types inside ducts. The proposed procedure was effective in classifying upper, internal, and delamination defects of ducts under 100 mm in thickness, and it could be utilized up to 200 mm in the case of duct defect limitations.


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