Pulsed Thermography Research Articles

Determination of thermal wave reflection coefficient to better estimate defect depth using pulsed thermography

Thermography is a promising method for detecting subsurface defects, but accurate measurement of defect depth is still a big challenge because thermographic signals are typically corrupted by imaging noise and affected by 3D heat conduction. Existing methods based on numerical models are susceptible to signal noise and methods based on analytical models require rigorous assumptions that usually cannot be satisfied in practical applications. This paper presents a new method to improve the measurement accuracy of subsurface defect depth through determining the thermal wave reflection coefficient directly from observed data that is usually assumed to be pre-known. This target is achieved through introducing a new heat transfer model that includes multiple physical parameters to better describe the observed thermal behaviour in pulsed thermographic inspection. Numerical simulations are used to evaluate the performance of the proposed method against four selected state-of-the-art methods. Results show that the accuracy of depth measurement has been improved up to 10% when noise level is high and thermal wave reflection coefficients is low. The feasibility of the proposed method in real data is also validated through a case study on characterising flat-bottom holes in carbon fibre reinforced polymer (CFRP) laminates which has a wide application in various sectors of industry.

Structural Health Monitoring (SHM) of Civil Structures

As newer and more reliable ways of construction were developed, civilization began to spread out further and retain functional infrastructure for longer periods of time.[...]

A study of pulsed thermography for life assessment of thin EB-PVD TBCs undergoing oxidation ageing

This paper presents an assessment of ageing for thin Thermal Barrier Coatings (TBC) using active thermography. As TBCs undergo ageing during their service life, sintering changes the porosity, elements migrate from the substrate, and micro-cracks build up in the structure of the material, exhibiting a change in thermal conductivity and diffusion properties. As the material ages and these properties change over time, it is possible to exploit trends in this change for characterisation of coating ageing, which would provide a diagnostics tool to estimate remaining useful life. In this study, through-depth diffusivity measurement has been applied to thin EB-PVD coatings which are artificially aged via oxidation furnace cycles. In order to address the difficulties of capturing a fast thermal event in a thin coating, a novel parametric study approach has been carried out to optimise data capture and analysis, maximising available frames for the model fitting step. Through-depth diffusivities have been measured during ageing for six samples, yielding a repeatable trend in thermal diffusivity measurements, with three features, which can be exploited for ageing characterisation of thin EB-PVD TBCs, and used as an alarm of imminent failure.

Thermography multidimensional manifold space projection and principal curves extraction for material state evaluation

Eddy current pulsed thermography (ECPT) has been extensively used for detection and evaluation of conductive material defect, in that spatial-transient-stage thermography implies crucial information about material properties. This paper presents a material state evaluation method using multidimensional manifold space projection and similarity measurement of principal curves to characterize and track the variation of material properties. The mathematical theories about manifold space projection and principal curves extraction have been introduced and the corresponding physical models are established. The simulations and real experiments are conducted to validate the proposed method. The combination of manifold learning method with ECPT has shown promising potential in characterizing and tracking material properties.

Pulse thermography identification of service insignia in Second World War camouflage German helmets

Abstract The present study aims at detecting and identifying the service insignia possibly present under the camouflage paint of Second World War German helmets, using infrared pulse thermography, a nondestructive IR technique based on the application of a short heat pulse, obtained by a flash lamp. While in most cases, IR thermography allowed to detect the insignia under the paint, in other cases sand, sawdust or woodchip added to the camouflage paint, in order to give it a rough and less reflecting texture, showed to be capable of preventing their detection. In 28.57% of the cases, the one or more layers of camouflage paint showed to be semi-transparent in the infrared waveband 3–5 μm, thus allowing to see not only the decal shape, but also the drawing inside the decal contour.

Thermal Analysis of Solder Joint Based on Eddy Current Pulsed Thermography

Solder joint provides electronic and mechanical connections between components and substrate. Overheating and excessive temperature gradient can cause solder joint failures and then make the whole system break down. Thus, thermal analysis has been the hotspot in reliability evaluation of electronic packaging. This paper proposes eddy current pulsed thermography (ECPT) to investigate thermal transfer through solder joint in a surface mounted device (SMD). A 3-D electromagnetic-thermal model was built, and the ECPT system was established to analyze transient temperature distribution on the pin surface. This model introduced pseudo soldering and evaluated its impacts on thermal conduction. Thermal resistance of solder joint was calculated to characterize different pseudo soldering defects. With pseudo soldering acreage increased, thermal resistance had an approximate quadratic rise. Both simulation and experimental results indicate that the surface temperature gradually decreases with the increase of pseudo soldering acreage. This ECPT method could be applied to the thermal analysis of solder joint in SMD, and it also could provide guidance for thermal design or reliability evaluation of electronic packages.

Comparative study of thermal contrast and contrast in thermal signal derivatives in pulse thermography

For detection of subsurface defects, flash thermography results are often evaluated by selecting the thermal image with the largest contrast between the sound and defective area. Another possibility is to calculate the logarithmic derivatives of the thermal signal, and evaluate the 1st or 2nd derivative images. In this paper, it is investigated how the contrast in these images depend on the defect size and defect depth. Analytical calculations and FEM simulations are presented, and based on these results equations for the contrast maxima are derived. Several advantages of the derivative images are shown; for example a defect with an aspect ratio around unity can be reliably detected in the derivative image, but not in the thermal image. To demonstrate these results experimental data are also presented.

Detection Mechanism of Parallel Defect using Scanning Inductive Thermography

Aiming at the requirement of workpiece integrity for parts processing line, on-line detection using inductive heating thermography for the moving workpieces on the assembly line is studied. In this paper, the detection mechanism of pulsed eddy current thermography for moving workpieces defects is analysed. A two-dimensional model of a magnetic material (45 steel), on which there is a crack parallel to the coil is established by the finite element software named COMSOL 5.2. By analysing the changes of the temperature curves, normalized curves and the temperature difference curves, the optimal detection area for parallel cracks is proposed. The consistency of the conclusions is verified by the experimental platform. The paper can provide a theoretical guidance for quantitative detection using eddy current thermography.

Characterization of defects of pulsed thermography inspections by orthogonal polynomial decomposition

Methods in infrared nondestructive testing such as normalized thermal contrast (NTC) and thermal signal reconstruction (TSR) are based on a pixel-by-pixel time domain analysis that ignores spatial correlation. Other techniques in the frequency domain such as pulsed phase thermography (PPT) present the same disadvantage. In this paper, we propose a method to evaluate defects in composite specimens based on image decomposition into a 2D orthogonal space. We compare NTC, TSR, PPT, and principal component thermography (PCT) with the new approach by inspecting three samples of composite anisotropic materials. Without defining a sound area our method estimates the depths of defects up to 1.2 mm in carbon and glass reinforced plastic specimens. An implementation of the proposed method in Matlab is available at https://github.com/charlielito/2DOrthogonal_Polynomial_Decomposition.

Non-destructive testing procedure for porosity determination in carbon fibre reinforced plastics using pulsed thermography

The aim of this work was to develop a procedure for the application of pulsed thermography as a quantitative method for porosity determination in carbon fibre reinforced polymers. Mathematical models are used to link the microstructural properties with global thermal properties which are the observation time and the thermal diffusivity. These detailed mathematical models, based on the effective medium theory, can be simplified for practical applications in the industry. It is possible to calculate a porosity image by the measurement of the thermal diffusion time. The predicted porosity image matches the measured porosity image based on cone beam X-ray computed tomography reference measurement quite well.

A Review of Microwave Thermography Nondestructive Testing and Evaluation.

Microwave thermography (MWT) has many advantages including strong penetrability, selective heating, volumetric heating, significant energy savings, uniform heating, and good thermal efficiency. MWT has received growing interest due to its potential to overcome some of the limitations of microwave nondestructive testing (NDT) and thermal NDT. Moreover, during the last few decades MWT has attracted growing interest in materials assessment. In this paper, a comprehensive review of MWT techniques for materials evaluation is conducted based on a detailed literature survey. First, the basic principles of MWT are described. Different types of MWT, including microwave pulsed thermography, microwave step thermography, microwave pulsed phase thermography, and microwave lock-in thermography are defined and introduced. Then, MWT case studies are discussed. Next, comparisons with other thermography and NDT methods are conducted. Finally, the trends in MWT research are outlined, including new theoretical studies, simulations and modelling, signal processing algorithms, internal properties characterization, automatic separation and inspection systems. This work provides a summary of MWT, which can be utilized for material failures prevention and quality control.

Sub-surface defects detection of by using active thermography and advanced image edge detection

Active or pulsed thermography is a popular non-destructive testing (NDT) tool for inspecting the integrity and anomaly of industrial equipment. One of the recent research trends in using active thermography is to automate the process in detecting hidden defects. As of today, human effort has still been using to adjust the temperature intensity of the thermo camera in order to visually observe the difference in cooling rates caused by a normal target as compared to that by a sub-surface crack exists inside the target. To avoid the tedious human-visual inspection and minimize human induced error, this paper reports the design of an automatic method that is capable of detecting subsurface defects. The method used the technique of active thermography, edge detection in machine vision and smart algorithm. An infrared thermo-camera was used to capture a series of temporal pictures after slightly heating up the inspected target by flash lamps. Then the Canny edge detector was employed to automatically extract the defect related images from the captured pictures. The captured temporal pictures were preprocessed by a packet of Canny edge detector and then a smart algorithm was used to reconstruct the whole sequences of image signals. During the processes, noise and irrelevant backgrounds exist in the pictures were removed. Consequently, the contrast of the edges of defective areas had been highlighted. The designed automatic method was verified by real pipe specimens that contains sub-surface cracks. After applying such smart method, the edges of cracks can be revealed visually without the need of using manual adjustment on the setting of thermo-camera. With the help of this automatic method, the tedious process in manually adjusting the colour contract and the pixel intensity in order to reveal defects can be avoided.

Using non-invasive non-destructive techniques to monitor cultural heritage objects

Cultural heritage plays a significant role in our identities and well-being. The aim of conservation is to manage change to cultural heritage objects. Non-destructive techniques offer an opportunity to quantify deterioration objectively and at an earlier stage than observation. There are limitations for using the techniques on precious artefacts. This paper examines some of the issues and opportunities through case studies with phased pulse thermography, acoustic emission, Fourier transform infrared spectroscopy and optical coherence tomography, applied to a series of mediaeval Limoges enamel plaques from the Werner Collection, displayed at Rangers House, London.

Evaluation of coating thickness by thermal wave imaging: A comparative study of pulsed and lock-in infrared thermography – Part I: Simulation

This paper investigates the possibilities of evaluating non-uniform coating thickness using thermal wave imaging method. A comparative study of pulsed thermography (PT) and lock-in thermography (LIT) based on evaluating the accuracy of predicted coating thickness is presented. In this study, a transient thermal finite element model was created in ANSYS 15. A single square pulse heating for PT and a sinusoidal heating at different modulation frequencies for LIT were used to stimulate the sample according to the experimental procedures. The response of thermally excited surface was recorded and data processing with Fourier transform was carried out to obtain the phase angle. Then calculated phase angle was correlated with the coating thickness. The method demonstrated potential in the evaluation of coating thickness and was successfully applied to measure the non-uniform top layers ranging from 0.1mm to 0.6mm; within an accuracy of 0.0003–0.0023mm for PT and 0.0003–0.0067mm for LIT. The simulation model enabled a better understanding of PT and LIT and provided a means of establishing the required experimental set-up parameters. This also led to optimization of experimental configurations, thus limiting the number of physical tests necessary.

An Investigation on Eddy Current Pulsed Thermography to Detect Surface Cracks on the Tungsten Carbide Matrix of Polycrystalline Diamond Compact Bit

Polycrystalline diamond compact (PDC) bits are commonly used drill bits in the petroleum drilling industry. Cracks often occur on the surface of a bit, which may result in the unexpected suspension of the drilling operation, or even accidents. Therefore, the detection of surface cracks on PDC bits is of great importance to ensure continuous drilling operation and to prevent accidents. However, it is extremely difficult to detect such cracks by visual inspection or other traditional nondestructive testing (NDT) techniques due to the small size of cracks and the irregular geometry of bits. As one emerging NDT technique, eddy current pulsed thermography (ECPT) can instantly detect surface cracks on metal parts with irregular geometry. In this study, the feasibility of ECPT of detecting surface cracks on the tungsten carbide matrix of PDC bits was investigated. A successive scanning detection mode is proposed to detect surface cracks by using ECPT with a low power heating excitation unit and small-size coils. The influence of excitation duration on the detection result was also investigated. In addition, principal component analysis (PCA) was employed to process the acquired IR image sequences to improve detection sensitivity. Finally, the whole shape of a crack was restored with processed images containing varied cracks segments. Based on the experimental results, we conclude that the surface cracks on the tungsten carbide matrix of PDC bit can be detected effectively and conveniently by ECPT in scanning mode with the aid of PCA.

Optimization of the Inspection of Large Composite Materials Using Robotized Line Scan Thermography

The emergence of composite materials has started a revolution in the aerospace industry. When using composite materials, it is possible to design larger and lighter components. However, due to their anisotropy, composite materials are usually difficult to inspect and detecting internal defects is a challenge. Line scan thermography (LST) is a dynamic thermography technique, which is used to inspect large components of metallic surfaces and composites, commonly used in the aerospace industry. In this paper, the robotized LST technique has been investigated on a large composite component which contains different types of internal defects located at a variety of depths. For theoretical analysis, the LST inspection was simulated using a mathematical formulation based on the 3D heat conduction equation in the transient regime in order to determine the optimum parameters. The solution of the model was performed using the finite element method. The LST parameters were adjusted to detect the deepest defects in the specimen. In order to validate the numerical results with experimental data, a robotized system in which the infrared camera and the heating source move in tandem, has been employed. From the experimental tests, it was noted that there are three sources of noise (non-uniform heating, unsynchronized frame rate with scanning speed and robot arm vibration) which affect the performance of the test. In this work, image processing techniques that were initially developed to be applied on pulse thermography have been successfully implemented. Finally, the performance of each technique was evaluated using the probability of detection approach.

Damage tolerance characterization of carbon fiber composites at a component level: A thermoset carbon fiber composite

This work focuses on the impact damage evaluation of a carbon fiber-reinforced thermoset composite at a component level (beams) as an effort to develop the service strategies for this class of materials. The beams were impact damaged at a variety of energy levels, and the pulse thermography nondestructive evaluation approach was used to characterize the damaged areas. The damaged beams were subjected to compression tests to evaluate their residual properties. As expected, both the beam maximum load and residual stiffness decreased with the increase in damage size. The damage growth rates under different load levels were investigated in fully reversed torsional fatigue tests. The fatigued beams were also characterized for their residual compression properties, which were then compared with those of the unfatigued beams. The results will be used to develop computer-aided engineering models to predict the residual strength and fatigue life of damaged composite components.

An improved feature extraction algorithm for automatic defect identification based on eddy current pulsed thermography

Abstract In this paper, an improved feature extraction algorithm in Eddy Current Pulsed Thermography (ECPT) is developed to realize automatic defect identification. The proposed feature extraction algorithm includes a data block segmentation, a variable interval search, a correlation value classification and a between-class distance decision function. The data block segmentation and variable interval search are firstly combined to reduce the repetitive calculation in automatic defect identification. The classification and between-class distance are used to select the typical features of thermographic sequence. The method is not only able to extract the main image information, but also can reduce the time of thermographic sequence processing to improve the detection efficiency. Experiments and comparisons are provided to demonstrate the capabilities and benefits (i.e. reducing the processing time) of the proposed algorithm in automatic defect identification.

A novel pulse compression algorithm for frequency modulated active thermography using band-pass filter

This paper proposes a novel pulse compression algorithm, in the context of frequency modulated thermal wave imaging. The compression filter is derived from a predefined reference pixel in a recorded video, which contains direct measurement of the excitation signal alongside the thermal image of a test piece. The filter causes all the phases of the constituent frequencies to be adjusted to nearly zero value, so that on reconstruction a pulse is obtained. Further, due to band-limited nature of the excitation, signal-to-noise ratio is improved by suppressing out-of-band noise. The result is similar to that of a pulsed thermography experiment, although the peak power is drastically reduced. The algorithm is successfully demonstrated on mild steel and carbon fibre reference samples. Objective comparisons of the proposed pulse compression algorithm with the existing techniques are presented.

Electromagnetic pulsed thermography for natural cracks inspection

Emerging integrated sensing and monitoring of material degradation and cracks are increasingly required for characterizing the structural integrity and safety of infrastructure. However, most conventional nondestructive evaluation (NDE) methods are based on single modality sensing which is not adequate to evaluate structural integrity and natural cracks. This paper proposed electromagnetic pulsed thermography for fast and comprehensive defect characterization. It hybrids multiple physical phenomena i.e. magnetic flux leakage, induced eddy current and induction heating linking to physics as well as signal processing algorithms to provide abundant information of material properties and defects. New features are proposed using 1st derivation that reflects multiphysics spatial and temporal behaviors to enhance the detection of cracks with different orientations. Promising results that robust to lift-off changes and invariant features for artificial and natural cracks detection have been demonstrated that the proposed method significantly improves defect detectability. It opens up multiphysics sensing and integrated NDE with potential impact for natural understanding and better quantitative evaluation of natural cracks including stress corrosion crack (SCC) and rolling contact fatigue (RCF).