Thermography For Nondestructive Evaluation Research Articles

Memory linked knowledge domain transfer few-shot learning for thermography nondestructive evaluation system

Infrared NDT techniques are suitable for detecting near-surface and sub-surface defects in composite materials. However, significant detection challenges remain while data volume is quantitatively limited for training weak contrast between defective and non-defective regions. In this paper, we propose an end-to-end memory linked knowledge domain with transfer few-shot learning segmentation network with a wider general model that solves the problems of insufficient data support. The proposed method is shown to attain high detection performance for multiple types of specimens by using cross domain adaption. By improving the support branch, a foreground-background joint guidance linked with memory bank is proposed. This provides better guidance information for the query branch. In addition, the intra-class and inter-class loss metric distance between defective and non-defective features is increased for better segmentation performance. In order to enable interpretability of the model, robust experiments have been conducted to detect the inner debond on multiple carbon fiber reinforced polymer (CFRP) composites. A comparative analysis is presented and compared with the state-of-the-art machine learning algorithms.

Characterization of drilling damage in glass laminate composites using lock-in thermography nondestructive evaluation method: a feasibility study

ABSTRACT The drilling of composite structure leads to its damage, near the peripheral areas of the drilled hole, due to the laminar structure of the composites. The goodness of a drilling process can be evaluated by measuring the extent of the damage caused by it. In the present study, lock-in thermography non-destructive inspection method is proposed to characterise the drilling damages in glass fiber–reinforced polymer panel. A semi-automated image processing methodology is proposed to calculate damage parameters, namely delamination area and size, and delamination factor. The effect of excitation frequency on the damage characterisation is studied to decide the optimum frequency range to measure the damage parameters through signal-to-noise ratio and damage visibility. The damage parameters are measured at optimum frequency. The study showed that the lock-in thermography technique has the potential to characterise drilling damage.

Lock-in thermography using miniature infra-red cameras and integrated actuators for defect identification in composite materials

A novel approach for thermographic Non-Destructive Evaluation (NDE) of laminated polymer composite structures is presented. The technique is based on Lock-In Thermography (LIT), which traditionally uses an external heat source. Here a new means of internal heating, via a lightweight embedded actuator capable of providing highly repeatable and uniform heating is presented. The equipment cost, complexity and hence size is reduced by removing the need for high power external thermal excitation. Instead, the necessary temperature modulation of the internal actuator is achieved with a compact and low-cost Arduino controlled circuit. The size and cost of the equipment is further reduced by demonstrating that a miniature printed circuit board mounted thermal core type micro-bolometer can be used effectively for LIT. The performance of the thermal core is quantitatively compared with the more expensive and bulky traditional infra-red cameras. It is shown that the thermal core can detect defects with similar overall performance as a cooled photon detector and an uncooled micro-bolometer. The low-cost, compact nature and small mass of the thermal core offers great potential in thermographic inspection opening the possibility of deploying devices permanently on structures in conjunction with the embedded actuators for in-situ monitoring in the service environment.

Defect Enhancement and Image Noise Reduction Analysis Using Partial Least Square-Generative Adversarial Networks (PLS-GANs) in Thermographic Nondestructive Evaluation

Defect Enhancement and Image Noise Reduction Analysis Using Partial Least Square-Generative Adversarial Networks (PLS-GANs) in Thermographic Nondestructive Evaluation

Induction Infrared Thermography for Non-destructive Evaluation of Welding-Induced Sensitization in Stainless Steels

For medium- and high-carbon stainless steels, welding can induce sensitization in the heat affected zone (HAZ) adjacent to the weld, where chromium carbide $$(\hbox {Cr}_{23}\hbox {C}_{6})$$ precipitates out of the bulk metal and accumulates at the grain boundaries. This chromium depletion and precipitate accumulation at grain boundaries makes the alloy susceptible to intergranular corrosion, environmentally assisted cracking, and broader fracture. In this paper, we investigate the efficacy of using induction infrared thermography (IIRT) as a non-destructive method for detecting welding-induced sensitization, using the AISI 440C steel as an example. We start by presenting a laboratory experiment to demonstrate this approach, using a radio frequency function generator, an induction wand, and a FLIR SC8203 infrared camera. We use traditional metallography techniques and scanning electron microscopy (SEM) to identify the location of any sensitized regions and characterize the corresponding microstructure. The IIRT experimental results reveal a distinguishable heat signature, with higher temperature observed within the sensitized regions. Next, we present a computational study to simulate the IIRT experiment and investigate the underlying physics. We adopt a three-dimensional thermo-electro-magnetic model including Fourier’s law of heat conduction and Maxwell’s equations for predicting the electromagnetic field caused by a sinusoidal excitation current flowing through the induction coil. We solve the system of governing equations using the commercial solver COMSOL Multiphysics. To numerically investigate the possible causes of the disproportionate heating within the sensitized regions, we realistically vary the values of electrical resistivity and magnetic permeability therein. The simulated results indicate that the heat signature observed in the laboratory experiment may result from the increase of both electrical resistivity and magnetic permeability in the HAZ. The possible physical relationships between sensitization and the variation of these two properties are discussed.

Nondestructive Evaluation of FRP-Concrete Interface Bond due to Surface Defects

Carbon fiber-reinforced polymer (CFRP) laminates have been successfully used as externally bonded reinforcements for retrofitting, strengthening, and confinement of concrete structures. The adequacy of the CFRP-concrete bonding largely depends on the bond quality and integrity. The bond quality may be compromised during the CFRP installation process due to various factors. In this study, the effect of four such construction-related factors was assessed through nondestructive evaluation (NDE) methods, and quantification of the levels of CFRP debonding was achieved. The factors were surface cleanliness, surface wetness, upward vs. downward application, and surface voids. A common unidirectional CFRP was applied to small-scale concrete samples with factorial combinations. Ground-penetrating radar and thermography NDE methods were applied to detect possible disbonds at CFRP-concrete interfaces. Thermography was found to clearly detect all four factors, while the GPR was only effective for detecting the surface voids only. The thermal images overpredicted the amount of debonded CFRP areas by about 25%, possibly due to scaling errors between the thermograph and the sample surface. The maximum debonded CFRP area in any sample was about two percent of the total CFRP area. This is a negligible amount of debonding, showing that the factors considered are unlikely to significantly affect the laminate performance or any CFRP contribution to the concrete member strength or confinement.

Ceramic Matrix Composite Materials for Engine Exhaust Systems on Next-Generation Vertical Lift Vehicles

Future gas turbine engines will operate at significantly higher temperatures (∼1800 °C) than current engines (∼1400 °C) for improved efficiency and power density. As a result, the current set of metallic components (titanium-based and nickel-based superalloys) will be replaced with ceramics and ceramic matrix composites (CMCs). These materials can survive the higher operating temperatures of future engines at significant weight savings over the current metallic components, i.e., advanced ceramic components will facilitate more powerful engines. While oxide-based CMCs may not be suitable candidates for hot-section components, they may be suitable for structural and/or exhaust components. However, a more thorough understanding of the performance under relevant environment of these materials is needed. To this end, this work investigates the high-temperature durability of a family of oxide–oxide CMCs (Ox–Ox CMCs) under an engine-relevant environment. Flat Ox–Ox CMC panels were cyclically exposed to temperatures up to 1150 °C, within 240 m/s (∼0.3 M) gas flows and hot sand impingement. Front and backside surface temperatures were monitored by a single-wavelength (SW) pyrometer and thermocouple, respectively. In addition, an infrared (IR) camera was used to evaluate the damage evolution of the samples during testing. Flash thermography nondestructive evaluation (NDE) was used to elucidate defects present before and after thermal exposure.

Combined experimental and computational approach for defect detection in precious walls built in indoor environments

In thermographic non-destructive evaluation (TNDE), the optimal thermal stimulus to be provided on precious coatings applied on ancient walls confined in indoor environments is a complex problem to solve particularly when low temperatures characterize the room where they were built. In fact, thermal stresses are always the concern of any restorer who is interested in determining both the positions and sizes of superficial and sub-superficial defects. In scientific literature, the use of lamps appears to be dominant, but when large surfaces must be inspected in situ, many problems could arise, such as environmental reflections, emissivity variations, and non-uniform heating, which cause false alarms in defect detections.In this study, the heating phase was carried out by using a wooden tunnel and an air heater. The main physical and geometrical characteristics of these two objects were optimized in order to stimulate the external coating (called “finishing layer” in this study) as homogeneously as possible. In fact, taking into account the very low temperature of the room which contains the inspected aedicule, the energy deposition (heating phase) is enhanced and the energy dispersion (cooling phase) is reduced (thanks to the tunnel) at the same time. This improves the heat transfer phenomenon along the z axis (i.e., the thickness of the wall).The detection of the defects was performed via higher-order statistics thermography (HOST) technique, which processes the thermal images resulting from the heating and cooling phases. Bearing in mind the low emissivity value of the canary grass (i.e., the finishing layer), the use of heating sources in front of it must be minimized; otherwise, spurious reflections can be recorded and then processed.In particular, a computational fluid dynamics (CFD) approach implemented via Comsol Multiphysics® computer program was used to validate the experimental setup. This was applied to a couple of cases in the Baiocco's room subjected to restrictions of the Superintendence for Historical, Architectural, and Environmental Heritage of the Abruzzo region (Italy) owing to its high artistic importance.The exact position of each defect was modelled after a combined visual-acoustical-thermal inspection. An expert restorer helped us in this task. This study is important because, to the best of our knowledge, the problem discussed above has not been solved yet by the scientific community involved in the field of cultural heritage. The results are first thoroughly discussed and second experimentally validated using a combination between thermocouples and ground penetrating radar (GPR) technique, while advantages and disadvantages of the proposed method are highlighted in view of a future perspective of the present work.

Thermographic Non-Destructive Evaluation for Natural Fiber-Reinforced Composite Laminates

Natural fibers, including mineral and plant fibers, are increasingly used for polymer composite materials due to their low environmental impact. In this paper, thermographic non-destructive inspection techniques were used to evaluate and characterize basalt, jute/hemp and bagasse fibers composite panels. Different defects were analyzed in terms of impact damage, delaminations and resin abnormalities. Of particular interest, homogeneous particleboards of sugarcane bagasse, a new plant fiber material, were studied. Pulsed phase thermography and principal component thermography were used as the post-processing methods. In addition, ultrasonic C-scan and continuous wave terahertz imaging were also carried out on the mineral fiber laminates for comparative purposes. Finally, an analytical comparison of different methods was given.

Ensemble variational Bayes tensor factorization for super resolution of CFRP debond detection

The carbon fiber reinforced polymer (CFRP) is widely used in aircraft and wind turbine blades. The common type of CFRP defect is debond. Optical pulse thermographic nondestructive evaluation (OPTNDE) and relevant thermal feature extraction algorithms are generally used to detect the debond. However, the resolution of detection performance remain as challenges. In this paper, the ensemble variational Bayes tensor factorization has been proposed to conduct super resolution of the debond detection. The algorithm is based on the framework of variational Bayes tensor factorization and it constructs spatial-transient multi-layer mining structure which can significantly enhance the contrast ratio between the defective regions and sound regions. In order to quantitatively evaluate the results, the event based F-score is computed. The different information regions of the extracted thermal patterns are considered as different events and the purpose is to objectively evaluate the detectability for different algorithms. Experimental tests and comparative studies have been conducted to prove the efficacy of the proposed method.

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.

Optimization of the pulse-compression technique applied to the infrared thermography nondestructive evaluation

Pulse-compression infrared thermography is an emerging nondestructive testing and evaluation technique. An analysis of the main issues hampering the full exploitation of this technique is presented from both theoretical and experimental point of view and various strategies are introduced to overcome these problems and optimize the defect detection performance. A comparison between conventional pulse-compression thermography procedures and the proposed one is reported, using an LED modulated with a Barker sequence as coded excitation, and a carbon fibre composite benchmark sample containing artificial defects at different depths. The experimental results show that the suggested signal processing procedure assures a higher SNR and hence an improved defect detection capability. In addition, a time-analysis of such signals allows the correlation between the depth of defects and heat diffusion time to be more clearly identified.

Non-uniformity correction and sound zone detection in pulse thermographic nondestructive evaluation

An important requirement in the thermographic nondestructive evaluation is the identification of actual sound zone or the base line with which the defective areas are compared to determine the actual temperature contrast and the corresponding defect severity. In a part under inspection, the actual sound zone is not known a priori and various approximations have been used in the past to serve as this unknown base line. Determination of actual sound zone in a defective test object is still a challenge. A related issue before the identification of this base line pixel is in the elimination of non-uniformity in the temperature distribution across the specimen surface which is unrelated to the actual defects. This spurious contrast is often introduced by the limitations of the instrumentation or the test procedure and it has to be eliminated before pixels in the sound zone can be located. This paper presents an automated procedure for simultaneously eliminating spurious contrast and locating sound zone pixels, directly from experimental data in a thermographic nondestructive evaluation. Location of actual sound zone pixels facilitates accurate thermal contrast computations, extraction of thermal properties such as break time and thermal diffusivity. In addition, based on the actual sound zone temperature profile it is possible to normalize experimental thermographic results in such a way that they can be directly correlated with results from numerical simulations.

A normalization procedure for pulse thermographic nondestructive evaluation

Pulse thermographic nondestructive evaluation (TNDE) technique can be used to estimate defect dimensions, and in particular the depth at which the defect is located. Numerical models of this procedure can aid in the interpretation of experimental results. However, the thermophysical properties of the test object as well as the amount of energy absorbed during this process are not readily available for such models. This paper presents an extension of the thermographic signal reconstruction (TSR) procedure in which the temperature and the time scales are respectively normalized with equilibrium temperature and the break time. In the normalized form these profiles are independent of material properties and instrumentation settings. Thus in the normalized format, experimental results can be readily compared with numerically generated thermographic results. The defect depth can also be easily obtained as a fraction of plate thickness from this plot.

Electromagnetic Thermography Nondestructive Evaluation: Physics-based Modeling and Pattern Mining.

Electromagnetic mechanism of Joule heating and thermal conduction on conductive material characterization broadens their scope for implementation in real thermography based Nondestructive testing and evaluation (NDT&E) systems by imparting sensitivity, conformability and allowing fast and imaging detection, which is necessary for efficiency. The issue of automatic material evaluation has not been fully addressed by researchers and it marks a crucial first step to analyzing the structural health of the material, which in turn sheds light on understanding the production of the defects mechanisms. In this study, we bridge the gap between the physics world and mathematical modeling world. We generate physics-mathematical modeling and mining route in the spatial-, time-, frequency-, and sparse-pattern domains. This is a significant step towards realizing the deeper insight in electromagnetic thermography (EMT) and automatic defect identification. This renders the EMT a promising candidate for the highly efficient and yet flexible NDT&E.

Thermographic Non-destructive Evaluation of Carbon Fiber-Reinforced Polymer Plates After Tensile Testing

Infrared thermography (IT) is a safe non-destructive evaluation technique that has a fast inspection rate and is generally contactless. It is used for diagnostics and monitoring in several fields including composite materials. In this paper carbon fiber-reinforced polymer plates submitted to tensile testing are inspected using IT. More specifically, carbon/polyether ether ketone panels made of random-oriented strands by compression moulding are submitted to tensile testing and then inspected using three different IT active approaches. The first two approaches use optical sources however with different scanning modes. The first active approach tested is a static surface scanning inspection in reflection mode. The second one is a dynamic line scanning technique where the energy source and camera are in movement with regards to the test sample. The last active IT approach tested uses a mechanical source (ultrasound excitation) to transfer heat to the sample being tested. This last approach is commonly called vibrothermography. Results obtained were then compared to results obtained by micro computed tomography inspection and microscopy. Results revealed voids associated with resin-rich regions as well as cracks.

Non-destructive evaluation of composite repairs by using infrared thermography

Composite structures are found in modern aircraft designs ranging from air transport to general aviation. Maintenance repair technology varies for each original equipment manufacturer and aircraft type. This research reports on two different composite repair methods commonly used within the composite aviation industry and how they compare when inspected with transient infrared thermography non-destructive evaluation technique. Composite sandwich test coupons made with carbon fiber laminate, nomex honeycomb, and glass fiber laminate were used for this work. Impact damages were generated in the sandwich test coupons and repairs were conducted by following repair procedures of two leading general aviation composite aircraft manufactures. During the repair process, controlled flaws were also induced to simulate bad repairs with weak bond areas, disbonds, and excessive porosity. During transient infrared thermography, several patches were identified that contained wrinkles, porosity, and disbond defects in the repaired panels. The indications were evaluated utilizing the time vs. temperature plot curves and profile data. The porosity indications displayed significant variations compared to the surrounding areas and were subsequently deemed defects as a result of the data.

Non-destructive evaluation system of metal materials according to thermal behaviours

The infrared thermography non-destructive inspection technique is a quality inspection and stability assessment method, which was used to diagnose the physical characteristics and defects by detecting the infrared ray radiated from the object without destructing it. The technique is being applied to diverse sectors. Its usage and importance increase with the development of the industrial areas that require high reliability and stability, including the semiconductor, nuclear power, defense, aerospace, and car industries. In this research, Ultrasound infrared thermography non-destructive evaluation system for metal materials according to thermal behaviours is established. To build ultrasound infrared thermography inspection system, infrared thermography test was performed by optimal design of the ultrasound excitation device and external energy control.

Transient Thermal Behavior of Eddy-Current Pulsed Thermography for Nondestructive Evaluation of Composites

Carbon fiber reinforced plastic (CFRP) materials are widely used in aircraft and wind turbine blades due to their low weight and high strength. Surface cracks, impact damages, and delaminations are the most common defects for CFRP composites. In this paper, the principal component analysis (PCA)-based eddy-current pulsed thermography method is proposed to detect and visualize defects from transient thermal images or videos. More specifically, three types of defects are classified based on their transient temperature behaviors using PCA at the pixel levels and optical flow patterns at the image levels. In addition, through feature extraction from optical flow method, the quantitative information about the defects, such as a defective area, is retrieved at the image levels.

An analytical study of the pulsed thermography defect detection limit

A simple modification of the one-dimensional expression for the thermal contrast of a layer provides a useful prediction of peak contrast temperature and contrast peak time for defects of all aspect ratios. The new analytical results have been shown to agree with numerical modelling. The thermographic nondestructive evaluation (NDE) rule-of-thumb that defects are detected if aspect ratio exceeds two is shown to have no general validity as peak contrast is found to depend critically on defect depth and absorbed excitation energy as well as defect aspect ratio. The effects of thermal diffusivity anisotropy are included in the analysis and illustrated by simulations of defect image contrast in composite materials.