This PDF file contains the front matter associated with SPIE Proceedings Volume 10214, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

This paper presents a synopsis and status of the various national and international standards relevant to thermal imaging and thermographers developed for the building, electrical, industrial, medical, and non-destructive testing industries. Particular detail will be given to newer and/or relevant to thermal imaging and thermographers within a wide variety of applications and disciplines. Common to most standards and guidelines are minimum performance requirements for the instrument, qualifications for the operator, and limitations of how thermal imaging should be applied.

This paper will summarize by discussing those areas and applications where development is still required. re-written standards that have come to be in the past 7 years, or are currently in development. These documents cut across a wide variety of agencies and disciplines, and nations often without regard for or knowledge of other similar standards or requirements. Agencies include but are not limited to the American Society for Test methods; American society for Non-Destructive Testing; Canadian Standards Association; International Standards organization; National Master Specifications of Canada (NMS) National Institute of Standards (NIST); and National Fire Prevention Association.

While standards, guidelines and protocols exist in many disciplines and industries, given the recent proliferation of low cost thermal imagers which are easily accessible to the public, it is important and appropriate that there be a widespread understanding of who, how , when, and where these imagers should properly be applied in order to obtain credible, scientific, and repeatable results. The best place to look for this understanding is through the knowledge and use of professional standards guidelines and protocols.

Adequate fire protection of distilled spirits stored in oak barrels requires understanding the failure mode of these barrels, including quantifying the leak rate. In this study, the use of a custom-calibrated, long-wave microbolometer camera is demonstrated to seek new protection methods for rack-stored distilled spirits. Individual oak barrels ranging between 200 L and 500 L filled with 75%/25% ethanol/water were exposed to both propane gas fires and pure ethanol pool fires. The IR camera was used to see through the smoke and flames showing the location of the leaks. The increase in HRR due to the leaked content was measured using gas calorimetry of the combustion products. This study showed that barrels leaked at a rate of approximately 4-8 lpm, resulting in heat release rates ranging between 1.2 and 2.4 MW. These numbers are confirmed by the quantitative measurements of gaseous H2O and CO¬2 in the exhaust. Surface temperature of the exposed oak could reach temperatures up to 750ºC.

Airborne thermal infrared (TIR) imaging systems are being increasingly used for wild fire tactical monitoring since they show important advantages over spaceborne platforms and visible sensors while becoming much more affordable and much lighter than multispectral cameras. However, the analysis of aerial TIR images entails a number of difficulties which have thus far prevented monitoring tasks from being totally automated. One of these issues that needs to be addressed is the appearance of flame projections during the geo-correction of off-nadir images. Filtering these flames is essential in order to accurately estimate the geographical location of the fuel burning interface. Therefore, we present a methodology which allows the automatic localisation of the active fire contour free of flame projections. The actively burning area is detected in TIR georeferenced images through a combination of intensity thresholding techniques, morphological processing and active contours. Subsequently, flame projections are filtered out by the temporal frequency analysis of the appropriate contour descriptors. The proposed algorithm was tested on footages acquired during three large-scale field experimental burns. Results suggest this methodology may be suitable to automatise the acquisition of quantitative data about the fire evolution. As future work, a revision of the low-pass filter implemented for the temporal analysis (currently a median filter) was recommended. The availability of up-to-date information about the fire state would improve situational awareness during an emergency response and may be used to calibrate data-driven simulators capable of emitting short-term accurate forecasts of the subsequent fire evolution.

Despite the broad application of the handheld thermal imaging cameras in firefighting, its usage is mostly limited to subjective interpretation by the person carrying the device. As remedies to overcome this limitation, object localization and classification mechanisms could assist the fireground understanding and help with the automated localization, characterization and spatio-temporal (spreading) analysis of the fire. An automated understanding of thermal images can enrich the conventional knowledge-based firefighting techniques by providing the information from the data and sensing-driven approaches. In this work, transfer learning is applied on multi-labeling convolutional neural network architectures for object localization and recognition in monocular visual, infrared and multispectral dynamic images. Furthermore, the possibility of analyzing fire scene images is studied and their current limitations are discussed. Finally, the understanding of the room configuration (i.e., objects location) for indoor localization in reduced visibility environments and the linking with Building Information Models (BIM) are investigated.

For process stability in laser powder bed fusion (LPBF) additive manufacturing (AM), control of melt pool dimensions is imperative. In order to control melt pool dimensions in real time, sampling frequencies in excess of 10 kHz may be required, which presents a challenge for many thermal and optical monitoring systems. The National Institute of Standards and Technology (NIST) is currently developing the Additive Manufacturing Metrology Testbed (AMMT), which replicates a metal based laser powder bed fusion AM process while providing open architecture for control, sensing, and calibration sources. The system is outfitted with a coaxially aligned, near-infrared (NIR) high speed melt pool monitoring (MPM) system. Similar monitoring systems are incorporated into LPBF research testbeds, and appearing on commercial machines, but at lower available frame rates, which may limit observation of higher frequency events such as spatter or size fluctuations. This paper presents an investigation of the coaxial imaging systems of the AMMT to capture the process dynamics, and quantify the effects of dynamic fluctuations on melt pool size measurements. Analysis is carried out on a baseline experiment with no powder material added, melt pool size measurements collected in-situ are compared to ex-situ measurements, and results are discussed in terms of temporal bandwidth. Findings will show that, even at the frame rate and resolution presented, challenges in relating in-situ video signals to the ex-situ measurement analysis remain.

Li-Metal oxides (typical example: lithium ortho-silicate Li₄SiO₄) are regarded as a novel solid carbon dioxide CO₂ absorbent accompanied by an exothermic reaction. At temperatures above 700°C the sorbent is regenerated with the release of the captured CO₂ in an endothermic reaction. As the reaction equilibrium of this reversible chemical reaction is controllable only by the partial pressure of CO₂, the system is regarded as a potential candidate for chemical heat storage at high temperatures.

In this study, we applied our recent developed mobile type instrumentation of micro-scale infrared thermal imaging system to observe the heat of chemical reaction of Li₄SiO₄ and CO₂ at temperature higher than 600°C or higher. In order to quantify the micro-scale heat transfer and heat exchange in the chemical reaction, the superimpose signal processing system is setup to determine the precise temperature.

Under an ambient flow of carbon dioxide, a powder of Li₄SiO₄ with a diameter 50 micron started to shine caused by an exothermic chemical reaction heat above 600°C. The phenomena was accelerated with increasing temperature up to 700°C. At the same time, the reaction product lithium carbonate (Li₂CO₃) started to melt with endothermic phase change above 700°C, and these thermal behaviors were captured by the method of thermal imaging. The direct measurement of multiple thermal phenomena at high temperatures is significant to promote an efficient design of chemical heat storage materials.

This is the first observation of the exothermic heat of the reaction of Li₄SiO₄ and CO₂ at around 700°C by the thermal imaging method.

After years of development, Fused Deposition Modeling (FDM) has become the most popular technique in commercial 3D printing due to its cost effectiveness and easy-to-operate fabrication process. Mechanical strength and dimensional accuracy are two of the most important factors for reliability of FDM products. However, the solid-liquid-solid state changes of material in the FDM process make it difficult to monitor and model. In this paper, an experimental model was developed to apply cost-effective infrared thermography imaging method to acquire temperature history of filaments at the interface and their corresponding cooling mechanism. A three-dimensional finite element model was constructed to simulate the same process using element "birth and death" feature and validated with the thermal response from the experimental model. In 6 of 9 experimental conditions, a maximum of 13% difference existed between the experimental and numerical models. This work suggests that numerical modeling of FDM process is reliable and can facilitate better understanding of bead spreading and road-to-road bonding mechanics during fabrication.

Lithium-ion batteries have become indispensable parts of our lives for their high-energy density and long lifespan. However, failure due to from abusive usage conditions, flawed manufacturing processes, and aging and adversely affect battery performance and even endanger people and property. Therefore, battery cells that are failing or reaching their end-of-life need to be replaced. Traditionally, battery lifetime prediction is achieved by analyzing data from current, voltage and impedance sensors. However, such a prognostic system is expensive to implement and requires direct contact. In this study, low-cost thermal infrared sensors were used to acquire thermographic images throughout the entire lifetime of small scale lithium-ion polymer batteries (410 cycles). The infrared system (non-destructive) took temperature readings from multiple batteries during charging and discharging cycles of 1C. Thermal characteristics of the batteries were derived from the thermographic images. A time-dependent and spatially resolved temperature mapping was obtained and quantitatively analyzed. The developed model can predict cycle number using the first 10 minutes of surface temperature data acquired through infrared imaging at the beginning of the cycle, with an average error rate of less than 10%. This approach can be used to correlate thermal characteristics of the batteries with life cycles, and to propose cost-effective thermal infrared imaging applications in battery prognostic systems.

Thermography and pattern classification techniques are used to classify three different pathologies in veterinary images. Thermographic images of both normal and diseased animals were provided by the Long Island Veterinary Specialists (LIVS). The three pathologies are ACL rupture disease, bone cancer, and feline hyperthyroid. The diagnosis of these diseases usually involves radiology and laboratory tests while the method that we propose uses thermographic images and image analysis techniques and is intended for use as a prescreening tool. Images in each category of pathologies are first filtered by Gabor filters and then various features are extracted and used for classification into normal and abnormal classes. Gabor filters are linear filters that can be characterized by the two parameters wavelength λ and orientation θ. With two different wavelength and five different orientations, a total of ten different filters were studied. Different combinations of camera views, filters, feature vectors, normalization methods, and classification methods, produce different tests that were examined and the sensitivity, specificity and success rate for each test were produced. Using the Gabor features alone, sensitivity, specificity, and overall success rates of 85% for each of the pathologies was achieved.

Biomedical infrared thermography, a non-invasive and functional imaging method, provides information on the normal and abnormal status and response of tissues in terms of spatial and temporal variations in body infrared radiance. It is especially attractive in cancer research due to the hypervascular and hypermetabolic activity of solid tumors. Moreover, healthy tissues like skin or mucosa exposed to radiation can be examined since inflammation, changes in water content, exudation, desquamation, erosion and necrosis, between others, are factors that modify their thermal properties.

In this work we performed Dynamic Infrared Imaging (DIRI) to contribute to the understanding and evaluation of normal tissue, tumor and precancerous tissue response and radiotoxicity in an in vivo model, the hamster cheek pouch, exposed to Boron Neutron Capture Therapy. In this study, we particularly focused on the observation of temperature changes under forced transient conditions associated with mass moisture transfer in the tissue-air interface, in each tissue with or without treatment. We proposed a simple mathematical procedure that considerers the heat transfer from tissue to ambient through convection and evaporation to model the transient (exponential decay o recover) thermal study. The data was fitted to determined the characteristic decay and recovery time constants of the temperature as a function of time. Also this model allowed to explore the mass flux of moisture, as a degree of evaporation occurring on the tissue surface. Tissue thermal responses under provocation tests could be used as a non-invasive method to characterize tissue physiology.

One of urgent security problems is a detection of objects placed inside the human body. Obviously, for safety reasons one cannot use X-rays for such object detection widely and often. For this purpose, we propose to use THz camera and IR camera.

Below we continue a possibility of IR camera using for a detection of temperature trace on a human body. In contrast to passive THz camera using, the IR camera does not allow to see very pronounced the object under clothing. Of course, this is a big disadvantage for a security problem solution based on the IR camera using. To find possible ways for this disadvantage overcoming we make some experiments with IR camera, produced by FLIR Company and develop novel approach for computer processing of images captured by IR camera. It allows us to increase a temperature resolution of IR camera as well as human year effective susceptibility enhancing. As a consequence of this, a possibility for seeing of a human body temperature changing through clothing appears.

We analyze IR images of a person, which drinks water and eats chocolate. We follow a temperature trace on human body skin, caused by changing of temperature inside the human body. Some experiments are made with observing of temperature trace from objects placed behind think overall. Demonstrated results are very important for the detection of forbidden objects, concealed inside the human body, by using non-destructive control without using X-rays.

In recent years, aperiodic, transient pulse compression favourable infrared imaging methodologies demonstrated as reliable, quantitative, remote characterization and evaluation techniques for testing and evaluation of various biomaterials. This present work demonstrates a pulse compression favourable aperiodic thermal wave imaging technique, frequency modulated thermal wave imaging technique for bone diagnostics, especially by considering the bone with tissue, skin and muscle over layers. In order to find the capabilities of the proposed frequency modulated thermal wave imaging technique to detect the density variations in a multi layered skin-fat-muscle-bone structure, finite element modeling and simulation studies have been carried out. Further, frequency and time domain post processing approaches have been adopted on the temporal temperature data in order to improve the detection capabilities of frequency modulated thermal wave imaging.

A composite fuselage aircraft forward section was inspected with flash thermography. The fuselage section is 24 feet long and approximately 8 feet in diameter. The structure is primarily configured with a composite sandwich structure of carbon fiber face sheets with a Nomex® honeycomb core. The outer surface area was inspected. The thermal data consisted of 477 data sets totaling in size of over 227 Gigabytes. Principal component analysis (PCA) was used to process the data sets for substructure and defect detection. A fixed eigenvector approach using a global covariance matrix was used and compared to a varying eigenvector approach. The fixed eigenvector approach was demonstrated to be a practical analysis method for the detection and interpretation of various defects such as paint thickness variation, possible water intrusion damage, and delamination damage. In addition, inspection considerations are discussed including coordinate system layout, manipulation of the fuselage section, and the manual scanning technique used for full coverage.

In this paper, thermographic inspections, ultrasonic C-scan and terahertz imaging were used to detect damages caused by impacts in natural, non-natural and hybrid composites. In particular, different hybrid structures were used. In some samples, numerical simulations were performed to predict the damage. A comparison of the results based on experimental and simulated experiments were afterwards conducted with the aim to explore the inspection capability of each technique.

Lock-in vibrothermography is used to characterize vertical kissing and open cracks in metals. In this technique the crack heats up during ultrasound excitation due mainly to friction between the defect’s faces. We have solved the inverse problem, consisting in determining the heat source distribution produced at cracks under amplitude modulated ultrasound excitation, which is an ill-posed inverse problem. As a consequence the minimization of the residual is unstable. We have stabilized the algorithm introducing a penalty term based on Total Variation functional. In the inversion, we combine amplitude and phase surface temperature data obtained at several modulation frequencies. Inversions of synthetic data with added noise indicate that compact heat sources are characterized accurately and that the particular upper contours can be retrieved for shallow heat sources. The overall shape of open and homogeneous semicircular strip-shaped heat sources representing open half-penny cracks can also be retrieved but the reconstruction of the deeper end of the heat source loses contrast. Angle-, radius- and depth-dependent inhomogeneous heat flux distributions within these semicircular strips can also be qualitatively characterized. Reconstructions of experimental data taken on samples containing calibrated heat sources confirm the predictions from reconstructions of synthetic data. We also present inversions of experimental data obtained from a real welded Inconel 718 specimen. The results are in good qualitative agreement with the results of liquids penetrants testing.

Carbon fiber-reinforced plastic (CFRP) is widely used for structural members of transportation vehicles such as automobile, aircraft or spacecraft, utilizing its excellent specific strength and specific rigidity in contrast with the metal. Short carbon fiber composite materials are receiving a lot of attentions because of their excellent moldability and productivity, however they show complicated behaviors in fatigue fracture due to the random fibers orientation. In this study, thermoelastic stress analysis (TSA) using an infrared thermography was applied to the evaluation of fatigue damage in short carbon fiber composites. The distributions of the thermoelastic temperature change was measured during the fatigue test, as well as the phase difference between the thermoelastic temperature change and applied loading signal. Evolution of fatigue damages was detected from distributions of thermoelastic temperature change according to the thermoelastic damage analysis (TDA) procedure. It was also found that fatigue damage evolution was clearly detected than ever by the newly developed thermoelastic phase damage analysis (TPDA) in which damaged area was emphasized in the differential phase delay images utilizing the nature that carbon fiber show opposite phase thermoelastic temperature change.

The use of wide frequency band piezoelectric transducers in ultrasonic infrared thermography allows analyzing material structural defects under low power ultrasonic stimulation compared to single-frequency stimulation which is performed, for example, by means of powerful magnetostrictive stimulation. Defect resonance frequencies can be determined through the detailed analysis of material surface vibrations by using a technique of laser vibrometry in a wide range of frequencies. This paper describes the approach to analyze ultrasonic resonances in samples with hidden defects by using resonant piezoelectric transducers. The effectiveness of the method is assessed by discussing some key examples of impact damaged graphite/epoxy composite samples hybridized with flax fibers. Optical and powerful ultrasonic stimulation have been also used as alternative inspection techniques.

Heat transfers are involved in many phenomena such as friction, tensile stress, shear stress and material rupture. Among the challenges encountered during the characterization of such thermal patterns is the need for both high spatial and temporal resolution. Infrared imaging provides information about surface temperature that can be attributed to the stress response of the material and breaking of chemical bounds. In order to illustrate this concept, tensile and shear tests were carried out on steel, aluminum and carbon fiber composite materials and monitored using high-speed (Telops FAST-M2K) and high-definition (Telops HD-IR) infrared imaging. Results from split-Hopkinson experiments carried out on a polymer material at high strain-rate are also presented. The results illustrate how high-speed and high-definition infrared imaging in the midwave infrared (MWIR, 3 – 5 μm) spectral range can provide detailed information about the thermal properties of materials undergoing mechanical testing.

Every year millions of people seek dental treatment to either repair damaged, unaesthetic and dysfunctional teeth or replace missing natural teeth. Several dental materials have been developed to meet the stringent requirements in terms of mechanical properties, aesthetics and chemical durability in the oral environment. Glass-ceramics exhibit a suitable combination of these properties for dental restorations. This research is focused on the assessment of the thermomechanical behavior of bio-ceramics and particularly lithium aluminosilicate glass-ceramics (LAS glass-ceramics). Specifically, methodologies based on Infrared Thermography (IRT) have been applied in order the structure – property relationship to be evaluated. Non-crystallized, partially crystallized and fully crystallized glass-ceramic samples have been non-destructively assessed in order their thermo-mechanical behavior to be associated with their micro-structural features.

In this work, the Thermographic technique (IRT) was used to characterize the fracture mechanics behaviour of stainless steels. In particular, IRT is proposed for evaluating the dissipated energy and the plastic area around the crack tip in order to study the fatigue crack growth.

Experimental approaches used for the measure of dissipated energy require an accurate equipment and suitable techniques that may restrict the applications just to laboratory tests. The proposed approach is based on thermal signal investigation in the frequency domain in order to separate the two heat sources related to the material behaviour during fracture mechanics test: thermoelastic sources and intrinsic dissipations. These latter are directly related to the plastic phenomena around the crack tip and occur at the twice of the loading frequency. Both amplitude and phase signals at the twice of the loading frequency can be used for evaluating the crack growth rate. In particular, the first index through an estimation of the heat dissipated while the second due to the effects occurring at the crack tip.

It was also demonstrated as the proposed approach is capable of monitoring the crack growth over time and in automatic way by means of such the contactless and full field technique.

Subsurface defects can be well detected by flash thermography evaluating the temperature response at the sample surface. In many cases flat bottom holes or air inclusions are investigated as typical defects. In contrast, in the current paper the main emphasis is placed on metal inclusions hidden in an insulator material. As the thermal effusivity of the metal is significantly higher than of the base material, the temperature decreases quicker above such a defect. Thermal quadrupole calculations and finite element simulations have been used to investigate more closely these temperature signals. Additionally, 3D printed samples have been created, where in the plastic material different metal plates, as steel, aluminum and copper have been introduced. The measurement results on these samples show very good agreement with theoretically calculated curves.

Pulsed Thermography (PT) is one of the most common methods in Active Thermography procedures of the Thermography for NDT & E (Nondestructive Testing & Evaluation), due to the rapidity and convenience of this inspection technique. Flashes or lamps are often used to heat the samples in the traditional PT. This paper mainly explores exactly the opposite external stimulation in IR Thermography: cooling instead of heating. A steel sample with flat-bottom holes of different depths and sizes has been tested. Liquid nitrogen (LN₂) is sprinkled on the surface of the specimen and the whole process is captured by a thermal camera. To obtain a good comparison, two other classic NDT techniques, Pulsed Thermography and Lock-In Thermography, are also employed. In particular, the Lock-in method is implemented with three different frequencies. In the image processing procedure, the Principal Component Thermography (PCT) method has been performed on all thermal images. For Lock-In results, both Phase and Amplitude images are generated by Fast Fourier Transform (FFT). Results show that all techniques presented part of the defects while the LN₂ technique displays the flaws only at the beginning of the test. Moreover, a binary threshold post-processing is applied to the thermal images, and by comparing these images to a binary map of the location of the defects, the corresponding Receiver Operating Characteristic (ROC) curves are established and discussed. A comparison of the results indicates that the better ROC curve is obtained using the Flash technique with PCT processing method.

The problem of moisture accumulation in airplane honeycomb panels is so serious that perspective aviation constructions could become monolithic or filled in with special foam. However, the number of airplanes with plentiful honeycombs under exploitation will keep very high in the few next decades. Therefore, quantitative water detection remains an actual task in aviation. The qualitative aspect of this problem can be solved by using the remote and fast technique of infrared thermography. Hidden water can be detected for a certain period of time after landing, or some stimulation heat sources can be used to enhance water visibility in honeycomb panels. However, quantitative evaluation of moisture content is typically achieved by applying a point-by-point ultrasonic technique which allows measuring the height of the water bar in single cells thus compiling maps of water distribution. This technique is contact and can be enough informative when applied to the water which is in contact with the panel skin because of gravitation. The use of solely infrared thermography for evaluating accumulated water mass based on the analysis of temperature patterns is difficult. Recently we found that there is a certain promise in the thermographic determination of water content, but the question is how precise (or how approximate) can be such estimates. The paper contains modeling and experimental results obtained in this direction.

Inductive thermography has been proved to be an excellent method for detecting surface cracks in metallic materials. The Joule heating is generated directly in the workpiece due to the induced eddy current and its penetration depth is determined by material properties and by the excitation frequency. Whether an additional temperature increase or a colder area around the crack occurs, is determined by the ratio of the crack depth to the penetration depth. It is investigated how material parameters, excitation frequency, crack depth and its inclination angle affect the temperature distribution around a crack after a short heating pulse. With finite element simulations material independent results are calculated showing in which frequency and temporal range crack detection is possible. These results are analyzed more closely for four selected metals: ferro-magnetic and non-magnetic steel, aluminum and titanium.

Thermal Barrier Coatings are used to protect the materials from severe temperature and chemical environments. In particular, these materials are used in the engineering fields where high temperatures, corrosive environments and high mechanical stress are required. Defects present between substrate material and coating, as detachments may cause the break of coating and the consequent possibility to exposure the substrate material to the environment conditions. The capability to detect the defect zones with non-destructive techniques could allow the maintenance of coated components with great advantages in terms of costs and prediction of fatigue life.

In this work, two different heat sources and two different thermographic techniques have been used to detect the adhesion defects among the base material and the coating. Moreover, an empirical thermographic method has been developed to evaluate the thickness of the thermal coating and to discriminate between an unevenness of the thickness and a defect zone. The study has been conducted on circular steel specimens with simulated adhesion defect and on specimens prepared with different thicknesses of thermal barrier coating.

Passive thermography has been shown to be an effective method for in situ and real time nondestructive evaluation (NDE) to measure damage growth in a composite structure during cyclic loading. The heat generation by subsurface flaw results in a measurable thermal profile at the surface. This paper models the heat generation as a planar subsurface source and calculates the resultant temperature profile at the surface using a three dimensional quadrupole. The results of the model are compared to finite difference simulations of the same planar sources.

The thermal diffusivity of solid materials is usually measured with the well-known flash method. In the traditional setup, the tested specimens have the shape of a small disc. However, several industrial applications need to test different typologies of samples. This work is focused on ring specimens, that are widely used as joints or sealants in various applications. The goal is investigating the possibilities and limitations of the flash method, applying minimum adjustments to the traditional experimental setup.

A preliminary numerical study is conducted with the creation of a finite element model. Firstly, the model is checked with the standard case of a full disk. Then the simulation investigates the case of an aluminum oxide ring, that is taken as the reference case to determine the reliability of the proposed technique.

After the simulation, an experimental measurement is performed on the aluminum oxide ring reference case. Several samples are tested and useful information on the practical feasibility of the experimental setup are collected. The obtained thermal diffusivity values fall into the expected range for the material, confirming the validity of the suggested method.

Aluminium alloys are here considered as a structural material for aerospace applications, guaranteeing lightness and strength at the same time. As aluminium alone is not particularly performing from a mechanical point of view, in this experimental solution it is produced as an alloy with Lithium added at 6 % in weight. To increase furtherly the strength of the material, two new alloys are produced by adding 0.5 % in weight of the rare earth elements Neodymium (Nd) and Yttrium (Y). The improvement of the mechanical properties is measured by means of hardness tests. At the same time the thermophysical properties are measured as well, at various temperature, from 80 °C to 500 °C. Thermal diffusivity is measured by Laser Flash equipment in vacuum. One possible drawback of the Al-Li alloy produced at so high percentage of Li (6 %) is an essential anisotropy that is evaluated by IR thermography thank to its imaging properties that allows to measure simultaneously both the in-plane and through-depth thermal diffusivity.

Pulse thermography or thermal wave imaging are commonly used as nondestructive evaluation (NDE) method. While the technical aspect has evolve with time, theoretical interpretation is lagging. Interpretation is still using curved fitting on a log log scale. A new approach based directly on the governing differential equation is introduced. By using relationships between wave propagation and the diffusive propagation of thermal excitation, it is shown that one can transform from solutions in one type of propagation to the other. The method is based on the similarities between the Laplace transforms of the diffusion equation and the wave equation. For diffusive propagation we have the Laplace variable s to the first power, while for the wave propagation similar equations occur with s². For discrete time the transformation between the domains is performed by multiplying the temperature data vector by a matrix. The transform is local. The performance of the techniques is tested on synthetic data. The application of common back projection techniques used in the processing of wave data is also demonstrated. The combined use of the transform and back projection makes it possible to improve both depth and lateral resolution of transient thermography.

Long term monitoring of transport infrastructures by infrared thermography has been studied and tested on different structures. A first standalone infrared system architecture developed is presented and discussed. Results obtained with such system on different Civil Engineering structures are presented. Some data processing approaches and inverse thermal model for data analysis are introduced and discussed. Lessons learned from experiments carried out in outdoor with such system are listed and analyzed. Then, a new generation of infrared system architecture is proposed. Finally, conclusions and perspectives are addressed.

The present study addresses the thermal behaviour of a modified pavement structure to prevent icing at its surface in adverse winter time conditions or overheating in hot summer conditions. First a multi-physic model based on infinite elements method was built to predict the evolution of the surface temperature. In a second time, laboratory experiments on small specimen were carried out and the surface temperature was monitored by infrared thermography. Results obtained are analyzed and performances of the numerical model for real scale outdoor application are discussed. Finally conclusion and perspectives are proposed.

Contactless temperature sensing is state of the art and essential part of countless applications in the field of process control and automation. This contribution presents the case of a nondestructive thickness measurement method for polymeric coatings on concrete ground. Two pyrometers and a low-cost infrared camera were taken into account. The particular measurement results were compared with those of a more sophisticated infrared camera. It was found that the low-cost infrared camera has a lower noise level than the pyrometers, even for a single pixel. The opportunity to average over a large number of pixels and to establish a bias correction enables a further noise reduction by almost factor of 10. Furthermore, the temporal resolution of the infrared camera was investigated by means of a well-defined thermal oscillation. It could be demonstrated that the averaged time stamps are correct and the requirement of a minimum framerate of 50 Hz is met. Finally, the temperature transient on a polymer coated concrete block during and after a 10 s heating period was recorded with a pyrometer and the infrared camera. This experiment confirmed the suitability of the camera for the intended measurement method.

A far-infrared (FIR) image contains important invisible information for various applications such as night vision and fire detection, while a visible image includes colors and textures in a scene. We present a coaxial visible and FIR camera system accompanied to obtain the complementary information of both images simultaneously. The proposed camera system is composed of three parts: a visible camera, a FIR camera, and a beam-splitter made from silicon. The FIR radiation from the scene is reflected at the beam-splitter, while the visible radiation is transmitted through this beam-splitter. Even if we use this coaxial visible and FIR camera system, the alignment between the visible and FIR images are not perfect. Therefore, we also present the joint calibration method which can simultaneously estimate accurate geometric parameters of both cameras, i.e. the intrinsic parameters of both cameras and the extrinsic parameters between both cameras. In the proposed calibration method, we use a novel calibration target which has a two-layer structure where thermal emission property of each layer is different. By using the proposed calibration target, we can stably and precisely obtain the corresponding points of the checker pattern in the calibration target from both the visible and the FIR images. Widely used calibration tools can accurately estimate both camera parameters. We can obtain aligned visible and FIR images by the coaxial camera system with precise calibration using two-layer calibration target. Experimental results demonstrate that the proposed camera system is useful for various applications such as image fusion, image denoising, and image up-sampling.

As microbolometer focal plane array formats are steadily decreasing, new challenges arise in correcting for thermal drift in the calibration coefficients. As the thermal mass of the cameras decrease the focal plane becomes more sensitive to external thermal inputs. This paper shows results from a temperature compensation algorithm for characterizing and radiometrically calibrating a FLIR Lepton camera.

Long Wavelength Infrared (LWIR) cameras can provide a representation of a part of the light spectrum that is sensitive to temperature. These cameras also named Thermal Infrared (TIR) cameras are powerful tools to detect features that cannot be seen by other imaging technologies. For instance they enable defect detection in material, fever and anxiety in mammals and many other features for numerous applications. However, the accuracy of thermal cameras can be affected by many parameters; the most critical involves the relative position of the camera with respect to the object of interest.

Several models have been proposed in order to minimize the influence of some of the parameters but they are mostly related to specific applications. Because such models are based on some prior informations related to context, their applicability to other contexts cannot be easily assessed. The few models remaining are mostly associated with a specific device.

In this paper the authors studied the influence of the camera position on the measurement accuracy. Modeling of the position of the camera from the object of interest depends on many parameters. In order to propose a study which is as accurate as possible, the position of the camera will be represented as a five dimensions model. The aim of this study is to investigate and attempt to introduce a model which is as independent from the device as possible.

Under development is a clinical software tool which can be used in the veterinary clinics as a prescreening tool for these pathologies: anterior cruciate ligament (ACL) disease, bone cancer and feline hyperthyroidism. Currently, veterinary clinical practice uses several imaging techniques including radiology, computed tomography (CT), and magnetic resonance imaging (MRI). But, harmful radiation involved during imaging, expensive equipment setup, excessive time consumption and the need for a cooperative patient during imaging, are major drawbacks of these techniques. In veterinary procedures, it is very difficult for animals to remain still for the time periods necessary for standard imaging without resorting to sedation – which creates another set of complexities. Therefore, clinical application software integrated with a thermal imaging system and the algorithms with high sensitivity and specificity for these pathologies, can address the major drawbacks of the existing imaging techniques. A graphical user interface (GUI) has been created to allow ease of use for the clinical technician. The technician inputs an image, enters patient information, and selects the camera view associated with the image and the pathology to be diagnosed. The software will classify the image using an optimized classification algorithm that has been developed through thousands of experiments. Optimal image features are extracted and the feature vector is then used in conjunction with the stored image database for classification. Classification success rates as high as 88% for bone cancer, 75% for ACL and 90% for feline hyperthyroidism have been achieved. The software is currently undergoing preliminary clinical testing.

Polyaniline is an organic intrinsically conductive polymer. With suitable doping it exhibits interesting values of both electrical conductivity and Seebeck coefficient, making it an interesting material for energy harvesting by conversion of heat energy in electric one in the range of temperature below 150 °C. The manufacturing of such material in thin and flexible sheets is furtherly interesting for a potential wearable use. Nonetheless, the value of thermal conductivity, that should be as low as possible to make more efficient the conversion, remains a challenging parameters to tune. IR thermography, thanks to its imaging capability, is an interesting instrument to conduct photothermal experiments that allow the characterization of thermal conductivity of these sheets, simultaneously through-the-thickness and in-plane.

In infrared thermographic testing, a background reflection is one of the main causes of a false detection. The authors developed an image processing program that can reduce the effect of the background reflection from a thermal image. The program mainly consists of two parts. The first part is the correction of emissivity which depends on a face angle. The emissivity is changed not only by a material property and a surface roughness but also by a face angle. Especially in a test for a high building and a floating roof tank, the thermal image includes a wide range of face angle. In order to solve this problem, by using the theoretical equation of emissivity, the angle correction of emissivity is carried out for each pixel in the infrared image. It is confirmed that the first part of this program can correct efficiently the emissivity change for a flat plate and a curved surface which have a wide range of face angle respectively. The second part of the program is the reduction of a background reflection. The emissivity change causes the reflectivity change and, as a result, this changes the effect of the background reflection. To reduce this effect, the background heat source is measured separately and then is subtracted from the infrared image. At this time, the specular reflectivity should be used. Consequently, this program can reduce the effect of reflection from the background heat source and extract the radiation of the flaw part from the complex thermal image.

System integrators are confronted with the challenge to implement various integrated detector cooler assemblies into their IR cameras. This paper will provide solutions for adjustable electrical and digital interfaces. The presented system design supports the control and frame processing of small detectors, e.g. with 320x256 pixels, as well as high-end detectors with a resolution up to 1,920x1,536. A 10 GigE camera interface to the PC provides a bandwidth of 10 GBit/s. It offers downwards compatibility to a 1GigE Interface without changing any hardware.

The applications of hyperspectral infrared imagery in the different fields of research are significant and growing. It is mainly used in remote sensing for target detection, vegetation detection, urban area categorization, astronomy and geological applications. The geological applications of this technology mainly consist in mineral identification using in airborne or satellite imagery. We address a quantitative and qualitative assessment of mineral identification in the laboratory conditions. We strive to identify nine different mineral grains (Biotite, Diopside, Epidote, Goethite, Kyanite, Scheelite, Smithsonite, Tourmaline, Quartz). A hyperspectral camera in the Long Wave Infrared (LWIR, 7.7-11.8 ) with a LW-macro lens providing a spatial resolution of 100 μm, an infragold plate, and a heating source are the instruments used in the experiment. The proposed algorithm clusters all the pixel-spectra in different categories. Then the best representatives of each cluster are chosen and compared with the ASTER spectral library of JPL/NASA through spectral comparison techniques, such as Spectral angle mapper (SAM) and Normalized Cross Correlation (NCC). The results of the algorithm indicate significant computational efficiency (more than 20 times faster) as compared to previous algorithms and have shown a promising performance for mineral identification.

Thermal and infrared imagery creates considerable developments in Non-destructive Testing (NDT) area. An analysis for thermal NDT inspection is addressed applying a new technique for computation of eigen-decomposition (factor analysis) similar to Principal Component Thermography(PCT). It is referred as Candid Covariance-Free Incremental Principal Component Thermography (CCIPCT). The proposed approach uses a computational short-cut to estimate covariance matrix and Singular Value Decomposition(SVD) to obtain faster PCT results, but while the dimension of the data increases. The problem of computational cost for high-dimensional thermal image acquisition is also investigated. Three types of specimens (CFRP, plexiglass and aluminum) have been used for comparative benchmarking. Then, a clustering algorithm segments the defect at the surface of the specimens. The results conclusively indicate the promising performance and demonstrated a confirmation for the outlined properties.

Fatigue limit estimation using infrared thermography has recently received attention as a method for reducing the time required for product design. In this study, the applicability of a method based on mean temperature and dissipated energy measurements was experimentally investigated on a titanium alloy; fatigue plate specimens were fabricated from the titanium alloy Ti-6Al-4V ELI. The fatigue limit of these specimens obtained from conventional fatigue testing was found to be 620 MPa. The estimated fatigue limit obtained from mean temperature measurements was found to be 600 MPa, although estimating the fatigue limit using dissipated energy measurements was difficult because little significant change in dissipated energy values with the stress amplitude was observed. These tendencies are probably attributed to the crystal structure displaying different deformation properties and high vibration absorption properties. The resonance components from the fatigue testing instruments (noise components) were calculated from the frequency analysis of the time-series temperature fluctuation data measured by infrared thermography. The increase in the dissipated energy values (with the noise components subtracted) against the stress amplitude changed at a certain stress amplitude and the fatigue limit could be estimated to be 565 MPa. Therefore, the relative error between the fatigue limit value obtained from conventional fatigue testing and the estimated values was within 10%. The fatigue limit could be estimated more accurately by considering the influence of different deformation properties between tensile and compressive loading due to the crystal structure differences in the dissipated energy measurement.

Hyperspectral imaging (HSI) in the long-wave infrared spectrum (LWIR) provides spectral and spatial information concerning the emissivity of the surface of materials, which can be used for mineral identification. For this, an endmember, which is the purest form of a mineral, is used as reference. All pure minerals have specific spectral profiles in the electromagnetic wavelength, which can be thought of as the mineral’s fingerprint. The main goal of this paper is the identification of minerals by LWIR hyperspectral imaging using a machine learning scheme. The information of hyperspectral imaging has been recorded from the energy emitted from the mineral’s surface. Solar energy is the source of energy in remote sensing, while a heating element is the energy source employed in laboratory experiments. Our work contains three main steps where the first step involves obtaining the spectral signatures of pure (single) minerals with a hyperspectral camera, in the long-wave infrared (7.7 to 11.8 μm), which measures the emitted radiance from the minerals’ surface. The second step concerns feature extraction by applying the continuous wavelet transform (CWT) and finally we use support vector machine classifier with radial basis functions (SVM-RBF) for classification/identification of minerals. The overall accuracy of classification in our work is 90.23± 2.66%. In conclusion, based on CWT’s ability to capture the information of signals can be used as a good marker for classification and identification the minerals substance.

There are numerous image fusion techniques such as intensity-hue-saturation (IHS) transform and principal component analysis (PCA). These methods are offering promising performance but the drawback with them is that they are not necessarily optimal in newer applications such as Ikonos and QuickBird. Color distortion is of vital importance in fusion image processing. The main result of this paper is the development of a fast HPM-enhanced version of the IHS method for application in fusion image processing in high-resolution satellite images. Combining these two methods makes it possible to benefit from the advantages of both methods. To evaluate the HPM-enhanced version of IHS method we used QuickBird data. The HPM-enhanced version of IHS and HPM-enhanced IHS are used interchangeably. The simulation results of this method show that it is capable of providing a significant improvement in preserving spectral and spatial information.