No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Reconstruction of size and depth of simulated defects in austenitic steel plate using pulsed infrared thermography
Abstract
In this paper the size and depth (distance from the tested surface) of defects in austenitic steel were estimated using pulse infrared thermography. The thermal contrast calculated from the surface distribution of the temperature is dependent on both these parameters. Thus, two independent experimental methods of defect size and depth determination were proposed. The defect size was estimated on the basis of surface distribution of the time derivative of the temperature, whereas the defect depth was assessed from the dependence of surface thermal contrast vs. cooling time.
... Pulse infrared thermography can effectively estimate the size and depth of defects. It is a non-contact testing with high inspection speed [8,9]. X-ray testing can efficiently detect hidden cracks, but it has negative effects on the human body [9]. ...
... It is a non-contact testing with high inspection speed [8,9]. X-ray testing can efficiently detect hidden cracks, but it has negative effects on the human body [9]. The application of eddy currents testing can be more significant with the reduction of the excitation frequency and the increase of the eddy current skin depth. ...
... However, the objective of the EC problem resolution is to solve Eqs. (8) and (9). The potential A (in the entire domain of the considered problem) and electric potential V (in the conductive regions of this domain) will be calculated. ...
Measuring and determining the parameters and characteristics of multilayer structures have become an important subject for several recent studies. This importance is due to industry needs and structural health requirements. The eddy current inspection is considered an important practical tool that ensures the safety and efficiency of multilayer structures and responds to the above necessities. The diversity of multilayer structure characteristics is one of the principal problems that must be solved. These physical and electromagnetic parameters are not always available or provided by the suppliers. Another problem that arises in the development of different models related to these structures is the difficulty of obtaining a satisfactory diagnosis. This difficulty returns to the complexity of geometry, the presence of small dimensions and sizes, and the existence of various parameters. In this context, it is necessary to achieve a strategy for the development of software and hardware tools concerning the characterization of multilayer structures. These tools must be applied to surmount the above problems and improve the technical advantages of the eddy current inspection. The principal objective of this work is to investigate the efficacy of the eddy current method applied to aeronautical materials, particularly low thickness multilayer structures. The modeling was performed using the finite element method. A software program was developed to investigate changes in the coil impedance. Results are initially validated and compared against the analytical and computational results given for simple cases. They are very similar, and they present a good agreement for both situations. The error is 5% for the calculus of the induction magnetic B. It also varies from 0.17% to 5.32% for impedance responses that enable the application of the developed code to carry out simulations for complex geometries. For various values of parameters and a wide range of applications, the parameters and properties of the problem can easily be introduced into the code. This permits the analysis and calculation of changes in impedance versus the effect of any variation in parameters. The developed approach is sufficiently general. It can simulate various potential cases of defects in low thickness multilayer structures due to its adequate design. It can generate interpretable results for different defect lengths and locations based on its fast computation and its ability to plot impedance responses. In addition, it can be used as a useful tool to assist students, engineers, and researchers in improving programs and materials related to eddy current inspection.
... Defect depth and residual thickness are two parameters that need to be resolved to characterise a defect. Many reports describe a positive relationship between defect depth, residual thickness, and the specific characteristic time of the inspected surface; however, most of these reports only consider defects at the sample-air interface [5,[11][12][13][14][15][16][17][18]. Externally corroded walls in buried pipes are not usually located at the sample-air interface. ...
... Size is another parameter that should be addressed when characterizing subsurface defects [2,5,9,17,[19][20][21]. However, there are few studies on the effect of defect interface on size estimation on the evaluation of subsurface defects. ...
... Methods for the estimation of the size of subsurface defects can be divided into two categories: (1) those that use surface profile of thermogram [2,17,19,23,24] and (2) those that use thresholding techniques [5,9,20,21,[25][26][27]. ...
This study characterized the in-pipe thermal signature of external pipewall thinning in steel pipes, a common problem that is caused by external corrosion in hostile underground environment. A model system was prepared to imitate the underground environment by milling several holes of various sizes and residual thicknesses into a mild steel plate. Wall thinning was investigated using active infrared thermography. The non-defective side of the steel plate was heated to 27.4 °C through the application of a thermal energy pulse while the ambient temperature was 22°C. Thermograms were captured inside the pipe at a frequency of 0.02 seconds for 5 min. The images of the thinned surface were processed in two steps. First, the peak contrast time algorithm was used to estimate the residual thickness. Second, Gaussian adaptive thresholding was used to estimate the size of the holes. The maximum observable defects had a diameter of 5 mm and a residual thickness of 3 mm. The type of defect interface (steel–sand or steel–air) had no significant effect on the estimation of residual thickness or size. This study developed a rapid approach in classifying defect's residual thickness by only utilizing two well-known parameters from infrared images – defect's peak thermal contrast and estimated area. Thus, the feasibility of non-destructive, in-pipe, quantitative IR thermographic analysis of buried metal pipelines is demonstrated.
... As required in ACI 318-05 (2014) [10] for building structures, the concrete cover thickness is at least 20 mm for structure not exposed to the weather or in contact with the ground, and 76 mm for concrete permanently exposed to the earth. Currently, among many NDTs, the active infrared thermography technique has been proven to be an effective tool to determine the location, and also the depth of delamination in concrete structures [6,[11][12][13]. This technique gives reliable results in the evaluation of the near-surface region with the depth of defects less than 10 cm [8,14]. ...
... In addition, the absolute contrast of each delamination is monitored to determine the observation time, propose the nondimensional prefactor k, and predict the depth of delamination. Currently, among many NDTs, the active infrared thermography technique has been proven to be an effective tool to determine the location, and also the depth of delamination in concrete structures [6,[11][12][13]. This technique gives reliable results in the evaluation of the near-surface region with the depth of defects less than 10 cm [8,14]. ...
... The mean absolute percentage error (MAPE) is commonly used to measure the differences between two datasets [42]; thus, it was applied in this study to assess the difference between the predicted depth and the real depth of defects. The MAPE can be defined by using Equation (13). ...
Detecting subsurface delamination is a difficult and vital task to maintain the durability and serviceability of concrete structure for its whole life cycle. The aim of this work was to obtain better knowledge of the effect of depth, heating time, and rebar on the detectability capacity of delamination. Experimental tests were carried out on a concrete specimen in the laboratory using Long Pulsed Thermography (LPT). Six halogen lamps and a long wavelength infrared camera with a focal plane array of 640 × 480 pixels were used as the heat source and infrared detector, respectively. The study focused on the embedded imitation delaminations with the size of 10 cm × 10 cm × 1 cm, located at depths varying from 1 to 8 cm. The signal-to-noise ratio (SNR) was applied as a criterion to assess the detectability of delamination. The results of this study indicate that as the provided heating time climbed, the SNR increased, and the defect could be identified more clearly. On the other hand, when using the same heating regime, a shallow delamination displayed a higher SNR than a deeper one. The moderate fall of the SNR in the case of imitating defect located below reinforced steel was also observed. The absolute contrast was monitored to determine the observation time, and the nondimensional prefactor k was empirically proposed to predict the depth of delamination. The mean absolute percentage error (MAPE) was used to quantitatively evaluate the difference between forecasted and real depth, which evaluation confirmed the high reliability of the estimated value of the prefactor k.
... Alternatively, the defect depth can be determined by using blind frequency in the pulse-phase thermography method [14] or by measuring the phase angle between incident radiation and surface temperature response via lock-in thermography [15]. Most of the methods require the knowledge about the exact size of the defect, as the determination of the time of maximum thermal contrast is not unique, defects from different depth may lead to the same SCT if they are of different size [16]. As an alternative, the logarithmic peak second derivative (LPSD) method, based on the one-dimensional heat transfer model can be used as a widely accepted method [11]. ...
... One possibility is the estimation of the defect size by investigating the distribution of the time derivative of the temperature over the surface of the sample [16]. First step is to find the maximum contrast between the defect area and the reference area. ...
... In case of deeper defects, all methods tend to give higher values than those in reality. It is therefore unclear whether the determination of defect size according to method (a) as used by [16] is transferable to CFRP. The methods (a) to (d) all have the disadvantage that the size is determined only in one profile. ...
... Therefore, if it is possible to evaluate CLP thinning defects using infrared thermography, quick and useful inspection will be possible. Reviewing the existing literature, it can be seen that various thermographic testing studies that simulated thinning defects have been conducted [13][14][15][16][17][18][19][20]. Representative Reviewing the existing literature, it can be seen that various thermographic testing studies that simulated thinning defects have been conducted [13][14][15][16][17][18][19][20]. ...
... Reviewing the existing literature, it can be seen that various thermographic testing studies that simulated thinning defects have been conducted [13][14][15][16][17][18][19][20]. Representative Reviewing the existing literature, it can be seen that various thermographic testing studies that simulated thinning defects have been conducted [13][14][15][16][17][18][19][20]. Representative examples include pulse thermography (PT) and lock-in thermography (LIT) using a light source as an external energy source, as well as static eddy current thermography and Appl. ...
This study presents a process for the quantitative investigation of thinning defects occurring in the containment liner plate (CLP) of a nuclear power plant according to various depths with a combined thermal wave signal and image processing in a lock-in thermography (LIT) technique. For that, a plate sample with a size of 300 × 300 mm was produced considering the 6 mm thickness applied to an actual CLP. The sample was designed with nine thinning defects on the back side with defect sizes of 40 × 40 mm and varying thinning rates from 10% to 90%. LIT experiments were conducted under various modulation frequency conditions, and phase angle data was calculated and evaluated through four-point method processing. The calculated phase angle was correlated with the defect depth. Then, the phase image was binarized by the Otsu algorithm to evaluate defect detection ability and shape. Furthermore, the accuracy of defect depth assessment was evaluated through third-order polynomial curve fitting. The detectability was analyzed by comparing the number of pixels of the thinning defect in the binarized image and the theoretical calculation. Finally, it was concluded that LIT can be applied for fast thinning defect detection and accurate thinning depth evaluation.
... Therefore, studies have been conducted to measure the depth of the defects by investigating the correlation between the temperature distribution and defect depth. [1,2] However, applicability of this method for sheet metals with thicknesses of 1 mm or less has not been verified. Therefore, in this study, the defect depth was estimated by using an equation that describes the relationship between the parameters derived from thermography and the defects. ...
... In addition, the difference in temperature is probably related to the defect size. The difference in temperature can be quantified by the standard thermal contrast C(t) and can be calculated by equation (1). [3] ...
... If a Dirac heat pulse is this excitation energy, a 1D solution of the Fourier equation can be found as the propagation of an ideal waveform defined as an intense unit-area pulse in a semi-infinite isotropic solid. Such solution has the form [14,15]: ...
... For comparison, an impulse of a xenon flash lamp was chosen as an alternative excitation source. In this experiment the impulse of 6 kJ energy and the 6 ms duration generated the power enough to register the temperature distribution on the surface of the sample and to visualize hidden defects by the IR camera according to Wysocka-Fotek et al. [15]. As shown in Fig 7, after the excitation of the sample by the xenon flash lamp the IR-camera registered only the first three largest holes with diameters d P 3 mm on the back side of the sample. ...
Specially created subsurface defects in a sample are detected using a high resolution infrared camera FLIR SC7000. A scanning hot air (about 110°C) nozzle is applied to introduce additional energy in a researched sample. The hidden defect has an increased temperature in comparison with the surrounding area that is a result of changed emissivity and thermal diffusivity. The suggested method is compared with pulse thermography which uses a xenon lamp for excitation.
... Thermography, and in general thermal imaging, has shown promise in several engineering applications. In material science, thermography was proved to detect defects in composite materials [15,16] and hidden corrosion in metals [17] and assess delamination in ceramic thermal coatings [1,18]. For instance, thermal imaging has been effectively utilized to detect the delamination of ceramic thermal barrier coatings in high-temperature turbine blades [19,20]. ...
Background: Accurate reconstruction of internal temperature fields from surface temperature data is critical for applications such as non-invasive thermal imaging, particularly in scenarios involving small temperature gradients, like those in the human body. Methods: In this study, we employed 3D convolutional neural networks (CNNs) to predict internal temperature fields. The network’s performance was evaluated under both ideal and non-ideal conditions, incorporating noise and background temperature variations. A physics-informed loss function embedding the heat equation was used in conjunction with statistical uncertainty during training to simulate realistic scenarios. Results: The CNN achieved high accuracy for small phantoms (e.g., 10 cm in diameter). However, under non-ideal conditions, the network’s predictive capacity diminished in larger domains, particularly in regions distant from the surface. The introduction of physical constraints in the training processes improved the model’s robustness in noisy environments, enabling accurate reconstruction of hot-spots in deeper regions where traditional CNNs struggled. Conclusions: Combining deep learning with physical constraints provides a robust framework for non-invasive thermal imaging and other applications requiring high-precision temperature field reconstruction, particularly under non-ideal conditions.
... Thermography and in general thermal imaging has shown promise in several engineering applications. In material science, thermography was proved to detect defects in composite materials [18,19], hidden corrosion in metals [20], and assess delamination in ceramic thermal coatings [1,21]. For instance, thermal imaging has been effectively utilized to detect the delamination of ceramic thermal barrier coatings in high-temperature turbine blades [22,23]. ...
In this study, we explore the use of 3D convolutional neural networks (CNNs) for predicting internal temperature fields from the surface temperature, with a focus on applications where small temperature gradients, similar to those in the human body, are present. The network accuracy was evaluated under both ideal and non-ideal conditions which include noise and background temperature effects. In non-ideal scenarios, the network accurately reconstructed the 3D temperature field for small phantoms (e.g., 10 cm in diameter). However, as the size of the domain increased, the network’s predictive capacity diminished, particularly in regions far from the surface. To address this limitation, we introduced statistical uncertainty during training, simulating non-ideal conditions, in combination with a physics-informed loss function which embed the heat equation directly into the training process. This combination can improve the model’s performance, particularly in noisy environments, where traditional CNN architectures failed to reconstruct hot-spots in deeper regions. Our results suggest that combining deep learning with physical constraints offers a robust framework for non-invasive thermal imaging and other applications requiring high-precision temperature field reconstruction.
... During LSP an elasticplastic wave changes surface layer and creates the compress residual stress that make it possible to use this phenomena for increase life time of materials and engineering construction. To date, non-destructive testing methods are widely used by various scientific groups to assess the condition of materials and structures [2,3]. ...
In this work a thermodynamic peculiarities of fatigue crack propagation at titanium alloy Ti64 after laser shock peening were studied. The plane samples were weakened by notch to initiate fatigue crack. An area around notch was processed by laser shock peening. This made it possible to create a compress residual stress up to 1 mm depth. The infrared thermography method was used to analyze a temperature field at crack tip. An increase in heat dissipation during fatigue crack propagation after laser shock peening was found.
... Optimization methods, e.g. least-squares [9], gradient search [10], Levenberg-Marquardt [11] can minimize the computed data with the experimental data through iterative calculation. By using optimization-based inversion algorithms, the defect parameters can be estimated by minimizing the error between the theoretical and predicted data. ...
Eddy current pulsed thermography (ECPT) is an effective non-destructive testing technique for evaluating the integrity and safe operation of conductive composite components such as carbon fibre reinforced polymer (CFRP) in aerospace applications. However, since any thermography technique measures a surface thermal distribution, ECPT does not directly provide comprehensive information at a layer level, e.g., about fibre orientation, which instead is important for indicating possible failures, e.g., fibre misalignment, debonding, etc. In this work, it is shown how ECPT data can be used to both reconstruct the layers’ orientation and to estimate the thermal and electrical conductivity of multilayer CFRP samples. This is achieved by implementing an iterative inversion procedure that processes experimental measurements together with finite element method simulations of the ECPT data. The procedure is applied to two multilayer CFRP samples with known plies orientations. Firstly, the electrical and thermal conductivities are estimated by the early experimental transient response of the first layer having a visible fibre’s orientation. Then, an iterative inverse procedure minimizes the discrepancy between measured and simulated data to reconstruct orientations of each layer using the estimated conductivity. Further, the results of this procedure are validated by exploiting a feature-based approach for orientations reconstructions, i.e. the Radon transform. It is also found that the error increase as the layer depth increases due to the diffusive nature of both electromagnetic and thermal waves.
... In addition, some methods based on the specific characterize time (SCT) were also proposed. SCT is normally chosen as the peak time of the 1st or 2nd derivative of the original temperature decay [9][10][11][12]. SCT can be classified in different ways. ...
The determination of defect depth is one of the important advantages of pulsed thermography. The existing methods for depth estimation in pulsed thermography are generally established based on the one-dimension heat conduction along the thickness of the sample. However, most of the methods neglect the effects of defect size and sample thickness, which induces additional systematic errors in depth estimation. In this study, simulations are conducted to demonstrate that the accuracy of depth determination of defects is greatly influenced by the defect size and sample thickness in some simulations. By establishing the relationship between the characteristic time and these factors, an accurate depth determination method based on the peak slope time is proposed. The proposed method has been applied to characterize the defect depths of a composite panel with flat-bottomed holes. The experimental results show that the use of the proposed method is able to identify the depths of defects with high accuracy.
... This is still a popular method being used for defects characterization [23,24]. Olga [25] improved the method by using the time derivative of the surface temperature distribution to determine the defect size through the half-height tangent method. Duan [26] demonstrated the use of the signal to noise ratio (SNR) analysis of the temperature distribution profile for the assessment of physical property of defects: when the SNR of the observed thermal anomaly is larger than 15, then the feature is considered as induced by defects. ...
A typical pulsed thermography procedure results in a sequence of infrared images that reflects the evolution of temperature over time. Many features of defects, such as shape, position, and size, are derived from single image by image processing. Hence, determining the key frame from the sequence is an important problem to be solved first. A maximum standard deviation of the sensitive region method was proposed, which can identify a reasonable image frame automatically from an infrared image sequence; then, a stratagem of image composition was applied for enhancing the detection of deep defects in the key frame. Blob analysis had been adopted to acquire general information of defects such as their distributions and total number of defects. A region of interest of the defect was automatically located by its key frame combined with blob analysis. The defect information was obtained through image segmentation techniques. To obtain a robustness of results, a method of two steps of detection was proposed. The specimen of polyvinyl chloride with two artificial defects at different depths as an example was used to demonstrate how to operate the proposed method for an accurate result. At last, the proposed method was successfully adopted to examine the damage of carbon fiber-reinforced polymer. A comparative study between the proposed method and several state-of-the-art ones shows that the former is accurate and reliable and may provide a more useful and reliable tool for quality assurance in the industrial and manufacturing sectors.
... Nevertheless, a wide variety of PT data processing techniques were developed to carry out qualitative and quantitative inspections. O. Wysocka-Fotek et al. [51] used standard thermal contrast method based on PT to estimate the size and depth of FBH defects in austenitic steel. X. Maldague et al. [52,53] combined the facets of PT and LIT techniques and proposed pulsed phase thermography (PPT). ...
This study performed an experimental investigation on pulsed thermography to detect internal defects, the major degradation phenomena in several structures of the secondary systems in nuclear power plants as well as industrial pipelines. The material losses due to wall thinning were simulated by drilling flat-bottomed holes (FBH) on the steel plate. FBH of different sizes in varying depths were considered to evaluate the detection capability of the proposed technique. A short and high energy light pulse was deposited on a sample surface, and an infrared camera was used to analyze the effect of the applied heat flux. The three most established signal processing techniques of thermography, namely thermal signal reconstruction (TSR), pulsed phase thermography (PPT), and principal component thermography (PCT), have been applied to raw thermal images. Then, the performance of each technique was evaluated concerning enhanced defect detectability and signal to noise ratio (SNR). The results revealed that TSR enhanced the defect detectability, detecting the maximum number of defects, PPT provided the highest SNR, especially for the deeper defects, and PCT provided the highest SNR for the shallower defects.
... Additionally, approaches for data reduction like higher order statistics [10] or principal component thermography [11] are possible. The depth of a defect underneath the surface is often determined, assuming a purely one dimensional heat-flux into the specimen, e.g. by using the method of specific characteristic time [12,13]. After pulsed excitation the time signal is differentiating twice, which leads to a considerable deterioration of the signal-to-noise ratio (SNR). ...
Infrared thermography (IRT) allows fast and cost-effective inspection of large structures made of carbon fibre reinforced polymer (CFRP) which must be checked for structural integrity after manufacture or during use. Due to its anisotropic and inhomogeneous microstructure, CFRP poses a major challenge for the quantitative determination of defects. In this paper we present a comprehensive full-factorial analysis of IRT data to verify the achievable accuracy of automated quantification of hidden defects of different size, shape and position in an inhomogeneous and anisotropic composite specimen, using pulse phase thermography.
... Defects such as delamination, erosion and cracks in composites pose a serious problem with regards to the safety and reliability of composites [5], and they are detected by different non-destructive means, such as ultrasonic and thermography methods [6][7][8]. Defect depth prediction is one of the important applications of non-destructive methods, and thermography is widely used in the detection and characterization of defects in composites through the reflection and transmission modes [9][10][11][12][13][14][15][16]. The transmission mode gives better thermal contrast in comparison to reflection mode for low-flash energy inputs [17]. ...
Defect depths are estimated in basalt fiber reinforced composite using long-pulse infrared thermography in the transmission mode. Defects of different sizes and depths are induced in the basalt fiber composite using flat-bottomed holes and their thermograms are analyzed. The contrast derivative and Parker’s method are used to predict the defect depths. The proportionality factor between peak contrast time and defect depth is determined analytically for the contrast derivative method. It is observed that the contrast derivative method predicts the defect depths and is independent of the defect sizes, whereas Parker’s method predicts deeper depth. The experimental results are in good agreement with the numerical results.
... A widely used method to determine the depth of a defect inside the sample is called Specific Characteristic Time (SCT) [10]. A characteristic time SCT or ...
... Defects such as delamination, erosion and cracks in composites pose a serious problem with regards to the safety and reliability of composites [5], and they are detected by different non-destructive means, such as ultrasonic and thermography methods [6][7][8]. Defect depth prediction is one of the important applications of non-destructive methods, and thermography is widely used in the detection and characterization of defects in composites through the reflection and transmission modes [9][10][11][12][13][14][15][16]. The transmission mode gives better thermal contrast in comparison to reflection mode for low-flash energy inputs [17]. ...
The long pulse thermography is a suitable technique for detection and quantification of defects in low thermal conducting materials, especially for composites. Basalt fiber reinforced epoxy composite is studied for determining defect depths using long pulse thermography. Flat bottom holes with specified depths and sizes are made in the composite for simulating delamination defects. Thermal images of the specimen are studied to obtain thermal contrast and characteristic peak time. A relation between the slope peak time and defect depth by peak derivative method is obtained analytically for long-pulsed thermography. Defect sizing is determined from the full- width- half- maximum approach. Experimental and numerical results are presented and analyzed.
... The active infrared thermography is a non-contact and non-destructive promising technique for perpend icular crack detection. It uses a local heating solicitation which can be continuous [1][2][3], pulsed [4][5][6][7][8] or modulated [9,10]. The disturbances of the heat diffusion produced by a crack which acts as a thermal barrier are then analyzed. ...
A crack located in the thermal diffusion zone of a heat source behaves like a thermal barrier modifying the heat diffusion. For a moving continuous source, the sample surface is heated on a little area near the crack for a duration which depends on the speed of the thermal source. A lock-in process synchronized by the displacement of the continuous heat source along the crack is studied. The thermal signature of the crack is extracted via a space operator applied to the amplitude and the phase of surface temperature images for various speeds of the thermal source. With the technical solution presented in this article, the thermal signature images are analysed according to a length representative of the thermal diffusion length to give a local evaluation of the crack depth (around 3 mm at the maximum) for crack lengths of about few centimetres long. The multi-speed lock-in thermography approach is initially studied with finite element method simulations. Experimental tests using an infra-red camera validate the method in a second part. The results do not depend on the heating source if its power is sufficient to produce a temperature rise detectable by an infra-red camera. The depth estimations are obtained independently of the crack width and heat source trajectory. The multi-speed lock-in thermography is a method without contact, without sample preparation, non-polluting, non-destructive and with simple optical adjustments.
... Quantitative estimation can be provided by using methods like ultrasonically stimulated thermography, eddy current stimulated thermography or laser thermographic imaging [2][3][4][5]. But these techniques, which are based on the analysis of the generated local rise of the crack temperature, need calibration procedures, a reference response and/or blackened sample to evaluate the crack depth [6][7][8][9][10][11][12][13][14][15][16]. ...
... The necessary conditions for IRNDT testing method are homogeneous thermal excitation of whole inspected surface, limited inspection depth combined with defects size and elimination of reflections from surrounding and/or thermal excitation source directly to the detector of IR camera. According to the application, a suitable combination of excitation method, analysis method and evaluation method including their parameters has to be found [4][5][6][7]. ...
Infrared non-destructive testing method (IRNDT) is suitable supplement to classic non-destructive testing
methods (NDT). The advantage of IRNDT method is fast and non-contact measurement and evaluation that is available
to various industrial and research applications. The method is suitable for both production process inspection (material
inhomogeneities, inner structure of multilayer parts, cracks, ...) and subsequent component inspection during service
(cracks, layers delamination, etc.) The possibility of defects detection is influenced by IRNDT method parameters,
geometric orientation of defects and by physical properties of material. The influence of material thermal properties on
the detectability of defects is discussed.
... We note that infrared thermography techniques [14][15][16][17][18][19][20][21][22][23] are somewhat related to thermal tomography, the main difference being that infrared thermography techniques are designed to detect defects that are located relatively close to the surface of the body, whereas thermal tomography aims at locating defects within the whole volume of the body and at giving quantitative solutions of the thermal conductivity and the heat capacity as well. ...
In a thermal tomography measurement setup, a physical body is sequentially heated at different source locations and temperature evolutions are measured at several measurement locations on the surface of the body. Based on these transient measurements, the thermal conductivity, the volumetric heat capacity and the surface heat transfer coefficient of the body are estimated as spatially distributed parameters, typically by minimizing a modified data misfit functional between the measured data and the data computed with the estimated thermal parameters. In thermal tomography, heat transfer is modeled with the time-dependent heat diffusion equation for which direct time domain solving is computationally expensive. In this paper, the computations of thermal tomography are sped up by utilizing a truncated Fourier series approximation approach. In this approach, a frequency domain equivalent of the time domain heat diffusion equation is solved at multiple frequencies and the solutions are used to obtain a truncated Fourier series approximation for the solution and the Jacobian of the time domain heat transfer problem. The feasibility of the approximation is tested with simulated and experimental measurement data. When compared to a previously used time domain approach, it is shown to lead to a significant reduction of computation time in image reconstruction with no significant loss of reconstruction accuracy.
... In FWHM, the width of half maximum gray level along horizontal and vertical lines in a selected IR thermal image is employed to describe the size of a defect. Olga et al. thus proposed a gradient-based sizing means for pulsed IR thermography, which is still widely being used today [16][17][18]. Maldague proposed a sizing method by computing the product of the derivative of contrast and contrast gradient in [13]. All of these approaches can size distinct defects with satisfactory accuracies. ...
We developed a new approach for sizing subsurface defects in the square pulse thermography of metallic plates by employing the oriented gradient of histograms. To size defects with high accuracies is still a challenge in infrared (IR) thermography today. Especially for blurry defects, accurate sizing of them is difficult with existing methods. The oriented gradient of histograms, which is used in the successful probability of boundary (Pb) contour detector in natural image processing literature, is employed in this work to improve the sizing accuracy in square pulse thermography. Experiments on a corroded steel plate with flat blind holes have verified the effectiveness of the proposed approach to size defects. Experimental results show that the proposed approach can size distinct and blurry defects with high accuracies. Comparison research is also implemented between the proposed approach and other sizing methods. The comparison results show that the proposed approach is superior to existing methods.
... The necessary conditions for IRNDT testing method are homogeneous thermal excitation of whole inspected surface, limited inspection depth combined with defects size and elimination of reflections from surrounding and/or thermal excitation source directly to the detector of IR camera. According to the application, a suitable combination of excitation method, analysis method and evaluation method including their parameters has to be found [4][5][6][7]. ...
Veselý Z., Švantner M.,Application of IRNDT method for materials in wide range of thermal diffusivity, Proc. of 13th Quantitative Infrared Thermography conference, QIRT 2016, July 4-8 2016, Gdansk, Poland, pp.267-268, 2016
Infrared non-destructive testing method (IRNDT) is suitable supplement to classic non-destructive testing
methods (NDT). The advantage of IRNDT method is fast and non-contact measurement and evaluation that is available to various industrial and research applications. The method is suitable for both production process inspection (material inhomogeneities, inner structure of multilayer parts, cracks, ...) and subsequent component inspection during service (cracks, layers delamination, etc.) The possibility of defects detection is influenced by IRNDT method parameters, geometric orientation of defects and by physical properties of material. The influence of material thermal properties on the detectability of defects is discussed.
... Quantitative estimation http can be provided by using methods like ultrasonically stimulated thermography, eddy current stimulated thermography or laser thermographic imaging [2][3][4][5]. But these techniques, which are based on the analysis of the generated local rise of the crack temperature, need calibration procedures, a reference response and/or blackened sample to evaluate the crack depth [6][7][8][9][10][11][12][13][14][15][16]. ...
The multi-frequency lock-in thermography is coupled with efficient image processing to analyse infrared open crack footprint. It has been shown that the evolution of the Laplacian of modulated surface temperature amplitude image as a function of the diffusion length allows to estimate the depth of surface open defects but requires calibration abacus obtained by finite element method simulations. In this work, a method is proposed to avoid the tedious use of abacus by introducing an indicator of the crack depth using a simple expression depending on the Laplacian of both amplitude and phase images. This multi-frequency method is presented through numerical simulations. Besides, the analysis of experimental results obtained on artificial and real open vertical cracks in metallic samples show that the depth of the defects can be directly estimated.
... In the first place, we consider the ferromagnetic material as the material under test. For an infinitely thick, semi-infinite ferromagnetic solid with a front surface that is instantaneously heated by a spatially uniform pulse, the surface temperature after heating is given by [25][26][27][28]: ...
... Unlike infrared thermography techniques [13][14][15][16][17][18][19][20][21][22] which are designed to detect defects that are located relatively close to the surface of the target medium, thermal tomography is a volumetric imaging technique which aims to locate defects within the whole target body as well as to give estimates of the thermal properties in the whole volume. ...
In this paper, feasibility of thermal tomography is tested using experimental measurement data. In the measurement setup, target volume is sequentially heated at different source locations and temperature evolutions are measured at several measurement locations on the surface of the volume. Based on these measurements, the thermal conductivity, volumetric heat capacity and surface heat transfer coefficient of the volume are estimated as spatially distributed parameters using the framework of Bayesian inversion. For the experimental measurements, a prototype measurement device was built and measurements were made of a mortar target containing an air filled cavity. As the estimates indicate the location of the cavity correctly, it is suggested that thermal tomography using experimental measurement data is feasible.
Purpose
Powder bed density is a key parameter in powder bed additive manufacturing (AM) processes but is not easily monitored. This research evaluates the possibility of non-invasively estimating the density of an AM powder bed via its thermal properties measured using flash thermography (FT).
Design/methodology/approach
The thermal diffusivity and conductivity of the samples were found by fitting an analytical model to the measured surface temperature after flash of the powder on a polymer substrate, enabling the estimation of the powder bed density.
Findings
FT estimated powder bed was within 8% of weight-based density measurements and the inferred thermal properties are consistent with literature findings. However, multiple flashes were necessary to ensure precise measurements due to noise in the experimental data and the similarity of thermal properties between the powder and substrate.
Originality/value
This paper emphasizes the capability of Flash Thermography (FT) for non-contact measurement of SS 316 L powder bed density, offering a pathway to in-situ monitoring for powder bed AM methods including binder jetting (BJ) and powder bed fusion. Despite the limitations of the current approach, the density knowledge and thermal properties measurements have the potential to enhance process development and thermal modeling powder bed AM processes, aiding in understanding the powder packing and thermal behavior.
Thermographic flash-pulse inspection is a popular technique of non-destructive testing (NDT) of carbon-fiber composites. Despite of an automation of the NDT methods, most of them are based on a visual inspection of indications and results of the inspections are thus influenced by the skills of operators. Repeatability and reproducibility (R&R) analysis of these inspections are therefore more important than in the case of exact gauge-type methods. This study was focused on statistical evaluation of flash pulse inspection. Space hardware representative carbon-fiber composite samples with 50 artificial defects were used as reference samples, which were independently inspected by three operators in two independent runs.Gauge R&R study was performed based on contrast to noise ratio and size of defects indications. It was determined, that, at certain conditions, a total Gage R&R variability 23% and 45% can be achieved for the diameter and the contrast to noise ratio evaluation, respectively.
This paper presents a method to quantify the geometry of defects such as flat bottom holes (FBH) and notches in opaque materials by a pulse thermography (PT) experiment and a numerical model. The aim was to precisely describe PT experiments in reflection configuration with a simple and fast numerical model in order to use this model and a fit algorithm to quantify defects within the material. The algorithm minimizes the difference between the time sequence of a line shaped region of interest (ROI) on the surface (above the defect) from the PT experiment and the numerical data. Therefore, the experimental data can be reconstructed with the numerical model. In this way, the defect depth of a notch or FBH and its width or diameter was determined simultaneously. A laser was used for heating which was widened to a top hat spatial profile to ensure homogeneous illumination (rectangular impulse profile in time). The numerical simulation considers heating conditions and takes thermal losses due to convection and radiation into account. We quantified the geometry of FBH and notches in steel and polyvinyl chloride plasticized (PVC-U) materials with an accuracy of <5 %.
In the previous chapter thermography has been shown to have potential for the identification of defects in adhesive bonds. The current chapter will initially provide an in depth review of the main types of thermography that use the addition of energy from light sources, namely pulsed, lock-in and pulse phase thermography. The types of detectors that may be used for these techniques are then considered. The underpinning physics of heat transfer that enables the detection of defects using thermography are then introduced before interpretation of the thermal data to extract estimated defect size is discussed. The practicalities of experimentation using thermography are then introduced including the experimental setup. Software and data collection and processing methods used in the current work are introduced and the importance of various variables studied. From this investigation knowledge of the importance of the experimental parameters is obtained and used in the remainder of experimental work.
The paper is devoted to reconstruction of size and depth (distance from the tested surface) of artificial defects with square and rectangular cross-section areas using the pulsed IR thermography. Defects in form of flat-bottom holes were made in austenitic steel plate. The defect size was estimated on the basis of surface distribution of the time derivative of the temperature. In order to asses the depth of defects with considered geometries on the basis of calibration relations (i.e. dependence of time of contrast maximum vs. defect depth for given defect diameter) obtained for circular defects, the ‘equivalent diameter’ describing not only the defect cross-section area but also its shape was assigned. It has been shown that presented approach gives satisfactory results.
Flash lamps are widely used excitation sources in the field of non-destructive testing with active thermography. Though the realized energy density in front of the investigated object is a significant factor with regard to detection sensitivity, only few data concerning this issue have been published so far. It is shown here that local energy densities can be estimated by means of a simple metal plate, which exhibits a certain temperature increase after flash excitation. After discussing the underlying calorimetric principle the sensor concept is reviewed using constant blackbody radiation and short laser pulses, since both kinds of sources generate known energy densities. The relative uncertainty of measurements of the energy density is found to be in the range of 10%. The last part of the present paper describes an application for characterizing the radiation of a usual 6 kJ flash lamp. The energy conversion efficiency was found to be only about 11%.
Results of researches are showed, that fabrication technology of sensor elements are used in devices based on surface plasmon resonance significantly affects on the increasing uptime of measuring and substantially increases the sensitivity to low concentrations of analytes. The results of investigations have shown that deposition of plasmonexciting metal layer on glass substrate at the chosen angle enables to enhance sensitivity of the surface plasmon resonance sensor by 1.5 times for liquid media and 2 times for gas-like media as compared with standard gold chips as well as improve uniformity of deposition and durability of ligand binding to the sensitive layer. Diagnostic facilities based on surface plasmon resonance possess a high sensitivity to low concentrations of studied substances, which enables one to use them as precise analytical devices in lab investigations in industry, agriculture, medicine, and ecology.
Standard thermal camera capabilities were extended for application in pulsed thermography, so that more accurate values of maximal temporal temperature difference, and therefore more reliable defect characterization, were acquired. This was achieved by fitting maximal values for temperature difference, extracted from successive frames, by a curve calculated with developed software based on thermal transport processes. Maximal temporal temperature difference is not possible to sample directly because it usually occurs between the frames. Thermal image processing and analysis were greatly simplified by specially prepared targets with periodic structure of defects. Developed numerical code can be further used to investigate defect detectability in different materials, but also to determine material thermal properties.
We present the mathematical model for simulation the heat conduction process in objects with buried defects. The model is based on the control volume numerical method. The simulation was carried out for defined start and boundary conditions on the model of known geometry and defects (cylindrical holes in different depths). The analysis was carried out in time and amplitude domain. The . results of the thermographic measurements taken on the real model having the same characteristic are given too. From the thermograms and numerical simulation the geometry of the defects is determined by means of the inverse procedure.
SYLRAMICTM continuous fiber ceramic-matrix composites (NicalonTM fiber/SiNC matrix) were fabricated by Dow Corning Corporation with the polymer-impregnation and pyrolysis (PIP) process. The composite macrostructure and its uniformity, and the completeness of infiltration during processing were studied as a function of number of PIP cycles. Two nondestructive evaluation (NDE) methods, i.e., infrared thermal imaging and air-coupled ultrasound (UT), were used to investigate flat composite panels of two thicknesses and various sizes. The thermal imaging method provided two-dimensional (2D) images of through-thickness thermal diffusivity distributions, and the air-coupled UT method provided 2D images of through-thickness ultrasonic transmission of the panel components. Results from both types of NDEs were compared at various PIP cycles during fabrication of the composites. A delaminated region was clearly detected and its progressive repair was monitored during processing. The NDE data were also correlated to results obtained from destructive characterization.
We describe the early time behavior of reflected thermal wave pulses from planar subsurface scatterers, and describe methods for making depth images, independently of the lateral size of the scatterer.
Details are presented of an experimental and theoretical investigation of the defect sizing capabilities of the transient thermography technique. Back-drilled hole artificial defects, of diameters from 2 to 10 mm and at depths between 0.5 and 1.7 mm, in bakelite plates, were thermographically imaged. Full-width at half maximum (FWHM) of a defect image is shown to be accurately related to defect diameter. These measurements are also shown to be in excellent agreement with finite-difference simulations of the response of this type of defect. The temporal dependences of the images are shown to provide an indication of defect depth.
Dynamic thermal tomography experiments were conducted on nonmetal
specimens (Delrin plastic and black organic glass) using a
computer-controlled system. The system consists of an infrared imager, a
microcomputer, a 25.6 kW pulsed heater, and a 60-Mb memory buffer. The
possibility of subdividing the plastic specimens into 8 layers up to a
depth of about 8 mm is demonstrated. The dynamic thermal tomography
algorithm used is briefly described.
An algorithm for the defect shape reconstruction from pulsed thermography data was developed. The aim was to reconstruct the defect shape in a test sample with known thermal properties. The algorithm consists of a defect shape correction unit and a simulation unit. The defect shape correction unit is designed to extract the defect shape roughly and refine it sequentially while the simulation unit models the heat conduction process in the inspected sample. The developed iterative algorithm is able to reconstruct 2D as well as 3D defect shapes. The algorithm was tested using experimental data obtained on a plate-shaped steel sample with a wall thickness profile. Robust defect shape reconstruction results were demonstrated.
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.
It is well known that the methods of thermographic non-destructive testing based on the thermal contrast are strongly affected by non-uniform heating at the surface. Hence, the results obtained from these methods considerably depend on the chosen reference point. The differential absolute contrast (DAC) method was developed to eliminate the need of determining a reference point that defined the thermal contrast with respect to an ideal sound area. Although, very useful at early times, the DAC accuracy decreases when the heat front approaches the sample rear face. We propose a new DAC version by explicitly introducing the sample thickness using the thermal quadrupoles theory and showing that the new DAC range of validity increases for long times while preserving the validity for short times. This new contrast is used for defect quantification in composite, Plexiglas™ and aluminum samples.
A data compression algorithm for the image sequences generated by pulsed-transient thermography for non-destructive testing was developed. The aim was to obtain a good compromise between reproduction of the original measurement data and a high compression factor. The algorithm for data compression comprises a dedicated space/time mapping (STM) method and an image compression algorithm (JPEG). The algorithm was tested on typical experimental thermography data. The results show a data storage compression factor of up to 24–55 at a reproduction accuracy which is still better than that achieved by an existing algorithm.
Scitation is the online home of leading journals and conference proceedings from AIP Publishing and AIP Member Societies
Infrared thermal imaging has become increasingly popular as a nondestructive evaluation method for characterizing materials and detecting defects. One technique, which was utilized in this study, is front-flash thermal imaging. We have developed a thermal imaging system that uses this technique to characterize advanced material systems, including continuous fiber ceramic composite (CFCC) components. In a front-flash test, pulsed heat energy is applied to the surface of a sample, and decay of the surface temperature is then measured by the thermal imaging system. CFCC samples with drilled flat-bottom holes at the back surface (to serve as “flaws”) were examined. The surface-temperature/time relationship was analyzed to determine the depths of the flaws from the front surface of the CFCC material. Experimental results on carbon/carbon and CFCC samples are presented and discussed.
The ability to predict subsurface defect information in composite materials through a non-invasive, efficient inspection protocol is fast becoming a vital research area. In numerically modeling the thermographic process associated with an infrared (IR) technique we can afford inspectors the ability to predict subsurface defect information associated with a specific material configuration. The research involved in this study looks specifically at the finite element modeling (FEM) of delaminations in a composite flat plate setup. To date the modeling of delaminations has been restricted to only two dimensional (2D) numerical representations and associated primarily with rear faced detection. The results of this research, however, clearly show that the rear faced detection technique has limitations in defect depth prediction and the 2D approximation associated with this technique ignores a paramount effect in the form of lateral thermal diffusion. It is also made clear that the representation of experimental flat plate models with flat bottomed holes, under pulse phase thermographic inspection, in simulating delaminations is misguided.
In this paper, a new absolute thermal contrast method is proposed for pulsed infrared thermography. It is based on the computations of reconstructed defect-free images so that no a priori knowledge of a sound area on the sample is necessary. Moreover, a correction is applied to take into account possible delays in the acquisition time. Results are presented both on Plexiglas TM and graphite-epoxy specimens. Comparisons with Pulsed Phase Thermography phase images are also presented along with a discussion on the advantages of the proposed method.
characterization The automatic detection of subsurface defects has become one desired goal in the application of Non Destructive Techniques. A new algorithm based on the Hough Transform, is proposed to reduce human intervention to a minimum by Pulsed Thermographic. The final result provided by this algorithm is an image showing the different defects without having attended to parameters so determinant in other algorithms as the delayed time of the first image or any subjective point of view in the analysis.
Numerical modelling of pulse thermography experiments using finite elements for purposes of defect characterization, Doctor's Thesis
- M Sus
M. Sus, Numerical modelling of pulse thermography experiments using finite elements for purposes of defect characterization, Doctor's Thesis, Quebec, Canada, 2009. pp. 82–89.
Theory and Practice of Infrared Technology for Nondestructive Testing
- X P V Maldague
X.P.V. Maldague, Theory and Practice of Infrared Technology for
Nondestructive Testing, Willey-Interscience, New York, 2001, pp. 198-199.
Experimental thermal tomography of solids by using the pulse one-side heating
- V P Vavilov
- T Ahmed
- H J Jin
- L R Favro
- L D Thomas
V.P. Vavilov, T. Ahmed, H.J. Jin, L.R. Favro, L.D. Thomas, Experimental thermal
tomography of solids by using the pulse one-side heating, Sov. J. Nondestruct.
Test. 12 (1990) 60-66.
Pulse-echo thermal wave imaging
- H X Favro
- X Han
- Y Wang
- P K Kou
- R L Thomas
H.X. Favro, X. Han, Y. Wang, P.K. Kou, R.L. Thomas, Pulse-echo thermal wave
imaging, in: D.O. Thompson, D.E. Chimenti (Eds.), Rev. Prog. Quant.
Nondestruct. Eval, Plenum Press, New York, 1995, pp. 425-430.
Numerical modelling of pulse thermography experiments using finite elements for purposes of defect characterization
- M Suśa
M. Suśa, Numerical modelling of pulse thermography experiments using finite
elements for purposes of defect characterization, Doctor's Thesis, Quebec,
Canada, 2009. pp. 82-89.