Image Enhancement in Transient Lock-In Thermography Through Time Series Reconstruction and Spatial Slope Correction
01 Apr 2012-IEEE Transactions on Instrumentation and Measurement (IEEE)-Vol. 61, Iss: 4, pp 1079-1089
TL;DR: An image reconstruction algorithm that enables LI thermography tests in the transient regime and removes temperature gradients due to nonuniform heating and surface emissivity variation is proposed.
Abstract: Lock-in (LI) thermography is a popular thermal-nondestructive-testing technique which, like other active thermographic techniques, requires an external heating stimulus, preferably on a blackened surface. It is not, however, immune to nonideal situations like nonuniform heating and surface emissivity variation. The phase image, to some extent, helps to reduce the effect of these artifacts but is inadequate if the variations are large. For example, a poorly blackened metallic sample with reflecting patches on its surface is very difficult to actively thermograph because of direct reflection from the surface. This paper proposes an image reconstruction algorithm for offline removal of such artifacts. In addition, the proposed algorithm enables LI thermography tests in the transient regime and removes temperature gradients due to nonuniform heating. The algorithm was tested with a mild-steel sample having 20-mm-diameter back-drilled holes at various depths ranging from 0.2 to 7.7 mm, stimulated at 20-, 40-, 50-, 60-, and 80-mHz excitation frequencies. The effect of the total number of heating cycles is also presented.
Citations
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TL;DR: A single-channel blind source separation is proposed to process the ECPT image sequences to automatically extract valuable spatial and time patterns according to the whole transient response behavior without any training knowledge.
Abstract: Eddy current pulsed thermography (ECPT) is an emerging nondestructive testing and evaluation (NDT&E) technique and has been applied for a wide range of conductive materials. In this paper, a single-channel blind source separation is proposed to process the ECPT image sequences. The proposed method enables: 1) automatically extract valuable spatial and time patterns according to the whole transient response behavior without any training knowledge, 2) automatically identify defect patterns and quantify the defects, and 3) to provide guidelines of choosing the optimal contrast functions that can improve the separation results. In this paper, both mathematical and physical models are discussed and linked. The basis of the selection of separated spatial and time patterns is also presented. In addition, an artificial slot and a thermal fatigue natural crack are applied to validate the proposed method.
126 citations
Cites methods from "Image Enhancement in Transient Lock..."
...Fourier transform-based frequency pattern extraction methods [14], [15] have been applied to pulsed thermography and enhanced the flaw-contrast significantly by using phase map....
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TL;DR: An integration of principal components analysis (PCA) and independent component analysis (ICA) on transient thermal videos has been proposed, which enables spatial and temporal patterns to be extracted according to the transient response behavior without any training knowledge.
Abstract: Eddy current pulsed thermography (ECPT) is implemented for detection and separation of impact damage and resulting damages in carbon fiber reinforced plastic (CFRP) samples. Complexity and nonhomogeneity of fiber texture as well as multiple defects limit detection identification and characterization from transient images of the ECPT. In this paper, an integration of principal component analysis (PCA) and independent component analysis (ICA) on transient thermal videos has been proposed. This method enables spatial and temporal patterns to be extracted according to the transient response behavior without any training knowledge. In the first step, using the PCA, the data is transformed to orthogonal principal component subspace and the dimension is reduced. Multichannel morphological component analysis, as an ICA method, is then implemented to deal with the sparse and independence property for detecting and separating the influences of different layers, defects, and their combination information in the CFRP. Because different transient behaviors exist, multiple types of defects can be identified and separated by calculating the cross-correlation of the estimated mixing vectors between impact the ECPT sequences and nondefect ECPT sequences.
110 citations
TL;DR: The proposed unsupervised method for diagnosing and monitoring defects in inductive thermography imaging system is fully automated and does not require manual selection from the user of the specific thermal frame images for defect diagnosis.
Abstract: This paper proposes an unsupervised method for diagnosing and monitoring defects in inductive thermography imaging system. The proposed method is fully automated and does not require manual selection from the user of the specific thermal frame images for defect diagnosis. The core of the method is a hybrid of physics-based inductive thermal mechanism with signal processing-based pattern extraction algorithm using sparse greedy-based principal component analysis (SGPCA). An internal functionality is built into the proposed algorithm to control the sparsity of SGPCA and to render better accuracy in sizing the defects. The proposed method is demonstrated on automatically diagnosing the defects on metals and the accuracy of sizing the defects. Experimental tests and comparisons with other methods have been conducted to verify the efficacy of the proposed method. Very promising results have been obtained where the performance of the proposed method is very near to human perception.
96 citations
Cites methods from "Image Enhancement in Transient Lock..."
...Infrared thermography can be used to assess and predict the structure or behavior beneath the surface by measuring the distribution of infrared radiation and converting the measurements into a temperature scale....
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TL;DR: In this article, a statistical method based on single channel blind source separation is proposed to decompose the two physical phenomena using different stages of eddy current and thermal propagation from the ECPT images.
Abstract: Eddy current pulsed thermography (ECPT) applies induction heating and a thermal camera for non-destructive testing and evaluation (NDT&E). Because of the variation in resultant surface heat distribution, the physical mechanism that corresponds to the general behavior of ECPT can be divided into an accumulation of Joule heating via eddy current and heat diffusion. However, throughout the literature, the heating mechanisms of ECPT are not given in detail in the above two thermal phenomena and they are difficult to be separated. Nevertheless, once these two physical parameters are separated, they can be directly used to detect anomalies and predict the variation in material properties such as electrical conductivity, magnetic permeability and microstructure. This paper reports physical interpretation of these two physical phenomena that can be found in different time responses given the ECPT image sequences. Based on the phenomenon and their behaviors, the paper proposes a statistical method based on single channel blind source separation to decompose the two physical phenomena using different stages of eddy current and thermal propagation from the ECPT images. Links between mathematical models and physical models have been discussed and verified. This fundamental understanding of transient eddy current distribution and heating propagation can be applied to the development of feature extraction and pattern recognition for the quantitative analysis of ECPT measurement images and defect characterization.
93 citations
TL;DR: A generative principal component thermography (GPCT) method for defect detection in polymer composites is proposed and more informative images are generated to enlarge the diversity of the original set of images.
Abstract: Machine learning methods play an important role in the nondestructive testing field for quality assessment of polymer composites. As a popular deep learning branch, a generative adversarial network is introduced to the thermography field as an image augmentation approach to improve its defect detection performance. Specifically, a generative principal component thermography (GPCT) method for defect detection in polymer composites is proposed. By employing the data augmentation strategy, more informative images are generated to enlarge the diversity of the original set of images. The defect detection results can be visualized using a number of interpretable features. Consequently, the defect detection performance of thermographic data analysis can be enhanced to some extent. The experimental results on a carbon fiber reinforced polymer specimen demonstrate the feasibility and advantages of the GPCT method.
74 citations
Cites methods from "Image Enhancement in Transient Lock..."
...Some methods mainly focus on noise reduction and/or background cancellation, including thermographic sequence reconstruction [5], [6], the Gaussian filtering [7], and differential absolute contrasting [8]....
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References
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Book•
30 Apr 2001
TL;DR: In this paper, the authors present an active and passive approach to active thermography for nondestructive testing of infrared sensors and Optic Fundamentals using Matlab M-Scripts.
Abstract: Preface. Getting Started with Thermography for Nondestructive Testing. FUNDAMENTAL CONCEPTS. Introduction to Thermal Emission. Introduction to Heat Transfer. Infrared Sensors and Optic Fundamentals. Images. Automated Image Analysis. Materials. Experimental Concepts. ACTIVE THERMOGRAPHY. Active Thermography. Quantitative Data Analysis in Active Thermography. ACTIVE AND PASSIVE THERMOGRAPHY: CASE STUDIES. Applications. References and Bibliography. Appendix A: Computer Model. Appendix B: Smoothing Routing. Appendix C: Parabola Computations. Appendix D: Higher-Order Gradient Computations Based on the Roberts Gradient. Appendix E: Properties of Metals and Nonmetals. Appendix F: Matlab M-Scripts Available. Index.
1,556 citations
"Image Enhancement in Transient Lock..." refers background in this paper
...Depending on the temporal nature of the applied IR heating, active thermography is broadly classified into pulsed thermography (PT) [1]–[3] and lock-in (LI) thermography [4], [5]....
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...On the basis of the source of heating, it is categorized into passive thermography and active thermography [1]....
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TL;DR: In this article, an approach combining both of pulse (PT) and modulated infrared thermography is proposed which combines simultaneously advantages both of PT and MODI, and the results are presented and the theory is discussed as well.
Abstract: An approach is proposed which combines simultaneously advantages both of pulse (PT) and modulated infrared thermography. In a nondestructive evaluation perspective, the specimen is pulse heated as in PT and the mix of frequencies of the thermal waves launched into the specimen is unscrambled by performing the Fourier transform of the temperature evolution over the field of view. Of interest is the maximum phase image with many attractive features: deeper probing, less influence of surface infrared and optical characteristics, rapid image recording (pulse heating, surface‐wide inspection), and the possibility to inspect high thermal conductivity specimens. Several results are presented and the theory is discussed as well.
918 citations
"Image Enhancement in Transient Lock..." refers methods in this paper
...This technique, popularly known as pulsed phase thermography [9]–[11], is used to improve the signal-to-noise ratio (SNR)....
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TL;DR: In this paper, the authors combined thermal wave and thermography to provide a short-time low-frequency phase angle image where non-thermal features can be suppressed using lock-in data analysis.
Abstract: Thermography and thermal wave techniques can be combined to provide in a short‐time low‐frequency phase angle images where nonthermal features can be suppressed. The principle is optical thermal wave generation simultaneously on the whole sample surface and sequential monitoring of all pixels using both thermographic techniques and lock‐in data analysis. Due to parallel stationary excitation one can use low modulation frequencies allowing for a depth range that is of relevance for applications.
638 citations
"Image Enhancement in Transient Lock..." refers background in this paper
...Depending on the temporal nature of the applied IR heating, active thermography is broadly classified into pulsed thermography (PT) [1]–[3] and lock-in (LI) thermography [4], [5]....
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TL;DR: In this paper, the authors proposed a deterministic active thermographic response is deterministic, to the extent that the postexcitation time evolution for a defect-free sample can be accurately predicted using a simple one-dimensional model.
Abstract: Active thermography has gained broad acceptance as a non- destructive evaluation method for numerous in-service and manufactur- ing applications in the aerospace industry. However, because of the dif- fusive nature of the process, it is subject to blurring and degradation of the signal as one attempts to image deeper subsurface features. Despite this constraint, active thermographic response is deterministic, to the extent that the postexcitation time evolution for a defect-free sample can be accurately predicted using a simple one-dimensional model. In the patented thermal signal reconstruction method, the time history of every pixel in the field of view is compared to such a model in the logarithmic domain, where deviations from ideal behavior are readily identifiable. The process separates temporal and spatial nonuniformity noise compo- nents in the image sequence and significantly reduces temporal noise. Time-derivative images derived from the reconstructed data allow detec- tion of subsurface defects at earlier times in the sequence than conven- tional contrast images, significantly reducing undesirable blurring effects and facilitating detection of low-thermal-contrast features that may not be detectable in the original data sequence. © 2003 Society of Photo-Optical In-
413 citations
"Image Enhancement in Transient Lock..." refers methods in this paper
...The temporal processing of PT data mainly involves first- and second-order time derivatives to enhance defect contrast [8]....
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TL;DR: In this paper, the phase sensitive modulation thermography (or "lock-in thermography") combines the advantages of photothermal radiometry with the fast technique of infrared imaging thereby revealing hidden defects in a short time.
312 citations
"Image Enhancement in Transient Lock..." refers background in this paper
...Depending on the temporal nature of the applied IR heating, active thermography is broadly classified into pulsed thermography (PT) [1]–[3] and lock-in (LI) thermography [4], [5]....
[...]
...The analysis of these thermograms mainly considers the phase shift of the thermal response of the defective regions with respect to the sound regions of the material [5]....
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