This PDF file contains the front matter associated with SPIE Proceedings Volume 10661, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

Current technologies for optical gas imaging use one of the following methods: (1) single band-pass filter, which dictate a “man in the loop” for detection; (2) bi-channel sensors that need allocation of half of the detecting area for each band; (3) low rate and/or highly expensive multi/hyperspectral sensors. We suggest a low-cost, fast electrically-switchable notch-filter, based on liquid crystal (LC) in an infrared (IR) transparent cell which enables dynamic dual band sensing on the entire detector area. We utilize fundamental properties of the LC: its molecular IR absorption bands (rovibrational modes) are overlapping those of gaseous (hydrocarbons, carbon dioxide , and more), and the transmittance of these bands depends on the orientation of the LC molecules relative to the polarization of the incident light (ordinary or extraordinary), Applying voltage on the LC cell affects the molecules' orientation, and therefore significantly changes the band transmittance. The high frequency response of LC cells to the electrical field enable detecting dynamic gas plumes. We proved this concept experimentally using custom made polyamide-coated Germanium cells and a commercial LC, E7. The spectral response, measured by a fast spectro-radiometer, for wavelengths between 2 to 14 micrometer, shows several absorption lines overlapping those of hydro-carbonates hazardous and greenhouse gaseous that require monitoring, and we demonstrated the detection of the refrigerant gas R-134a. We are currently preforming an experimental imaging setup for gas detection based on this method, and the results will be presented in this talk.

In the case of accidental methane leakage on a gas production industrial site, it is essential that the risks associated with an explosion of escaped clouds are assessed. By combining spectral and spatial information, hyperspectral technology is an attractive solution for the detection of such a cloud and for the quantification of its concentration. Total has started in 2014 a research program in partnership with Onera, called NAOMI (New Advanced Observation Methods Integration) to develop new tools for remote characterization of accidental methane plumes, especially over areas inaccessible to the personnel. From one of the results of this partnership, Onera is developing an algorithm, IMGSPEC, especially designed for this purpose, using hyperspectral acquisitions in the LWIR domain. The principle of IMGSPEC consists of estimating the spectral transmission of the gas cloud using an image of the background. An acquisition image of the same scene without gas is not necessarily available however. The strong point of the algorithm is its ability to recover the signal of the background. The integrated concentration is subsequently estimated pixel by pixel constituting a ppm.m concentration map. Finally, the flow rate of the leak is calculated considering the mass of the cloud, combining concentration estimation and methane density, and the wind speed which is measured with a meteo-station for instance. This algorithm was tested in June during a specific test campaign on the Lacq platform, a Total R and D industrial site. Methane leaks have been performed regulating the following flow rates: 1g/s, 10 g/s and 100g/s. Flow rate was estimated by IMGSPEC in near real-time following hyperspectral datacube acquisitions. Acquisition and processing times were both 4s, constituting a global flow rate estimation time below 10s

The hyperspectral chemical mapping of open mines exploited by industries are among the possible applications that could possibly benefit from thermal infrared long-distance survey. More specifically the cement production essential in the constructions of our cities. The cement is made by mixing different raw materials and firing them in order to achieve precise chemical proportions of lime, silica, alumina and iron in the finished product. The quality of cement is therefore directly related to the chemistry of the raw materials used. Approximately 80 to 90% of the raw material is limestone. Clayey raw material accounts for between 10 to 15%, although precise amounts vary. Magnesium carbonate, which may be present in limestone, is the main undesirable impurity. The level of magnesia (MgO) should not exceed 5% and many producers prefer a maximum of 3%; this excludes dolomite or dolomitic limestones for the manufacture of cement. In this work, we conducted thermal infrared (TIR) hyperspectral imaging for mineral mapping and mineralogy identification on a pit wall with Juracement at Cornaux using hyperspectral camera. This passive thermal infrared hyperspectral research instrument based on Fourier transform spectroscopy provides high spectral resolution data. The solid targets such as minerals not only emit but also reflect thermal infrared radiation. Since the two phenomena occur simultaneously, they end-up mixed in the radiance measured at the sensor level. To unveil the spectral features associated with minerals from TIR measurements, the respective contributions of self-emission and reflection in the measurement must be «unmixed» using temperature-emissivity separation (TES) algorithms. We developed a new TES procedure that allowed us to retrieve the spectral emissivity of the different minerals in the investigated scene. The chemical maps of the calcite dolomite mixtures were obtained on the pit wall the investigations were carried out, giving important insights on chemical the quality of the mine.

Wildland fires are considered one of the major natural risks affecting almost every country in the world. The impacts of these fires are huge in term of environmental, economic, and social losses. Experts estimate that with the climate change and global warming, we will witness an increase in the frequency and size of fires in the next years. In this paper, we will present the advances in the use of multiple spectrum computer vision to process, analyze and understand wildland fires behavior. We will introduce different multispectral technologies used in image capture, the techniques developed to detect and extract the fires from the images, and how multispectral fusion is used in the context of wildland fires. We will show our recent results using multiple multimodal stereovision systems where different modalities are combined to extract important fires characteristics in threedimensional space. Finally, we will discuss the use of UAVs to monitor fires at a larger scale.

Correct emittance value is one of the necessary inputs for accurate radiometric temperature measurement. Modern Infrared cameras and/or radiometric software programs typically have default emittance tables built-in allowing the operator to simply select the appropriate material and its corresponding emittance value. Unfortunately, many of these values, while perhaps accurately obtained in a laboratory setting, are typically not appropriate for use in a real-world field environment. There are many reasons for this which include: the deposition of dust, dirt and grease; the unknown thickness of oxide layers; the use of invisible (to the human eye) coatings, the unknown nature of the exact material or alloy; an incorrect value in the table itself due to wavelength or test method; and the effect of surface roughness, geometry, cavity radiation, spatial resolution, angle of view or temperature. In many situations incorrect selection of emittance value results in two miscalculations which can magnify the temperature measurement error significantly: calculation of surface reflectance value which in-turn calculates the amount of background signal to be subtracted from the radiance signal; and correction of the remaining signal attributable to radiant spectral exitance to that of the blackbody equivalent signal determined by the camera calibration. This paper will discuss these issues in depth, provide practical considerations for the field use of emittance, and present a simple method to determine measurement errors due to the unknown variance of emittance.

Gas leaks and air pollution sources present to a certain extend health, safety and environmental risks. A history of crisis management in the Upstream has shown the value of efficient and accurate tools for detecting gas leakages and/or the characterization air pollution agents. Knowing about the existence of a leak or the existence of an environmental thread is not always enough to launch a corrective action. Additional critical inputs such as the leak source, the chemical nature of the gas cloud, its direction and speed and as well as the gas concentration must most of the time be gathered in a short amount of time to help securing the hazardous areas. Most of the time gas identification for gas leaks surveys or environmental monitoring purposes involve explosives and/or toxic chemicals. In such situations, airborne measurements present particular advantages over ground based-techniques since large areas can be covered efficiently from a safe distance. In this work, we present our recent results on real time airborne gas detection up to 4600 feet above the ground using thermal hyperspectral Imaging technology. The Fourier transform technology used in the longwave (8-12 micron) hyperspectral camera on an airborne platform allows recording of airborne hyperspectral data using mapping and targeting modes. These two acquisition modes were used for gas imaging a ground-based ethylene, Methanol and acetone gas release experiment. Real time quantitative airborne chemical images of the three gas clouds were obtained paving the path toward a viable solution for gas leak surveys and environmental monitoring.

Extracting face images at a distance, in the crowd, or with a lower resolution infrared camera leads to a poorquality face image that is barely distinguishable. In this work, we present a Deep Convolutional Generative Adversarial Networks (DCGAN) for infrared face image enhancement. The proposed algorithm is used to build a super-resolution face image from its lower resolution counterpart. The resulting images are evaluated in term of qualitative and quantitative metrics on infrared face datasets (NIR and LWIR). The proposed algorithm performs well and preserves important details of the face. The analysis of the resulting images show that the proposed framework is promising and can help improve the performance of image super-resolution generation and enhancement in the infrared spectrum.

The paper describes efforts to establish traceable measurements of radiance temperature on laser-induced heated metal surfaces on the NIST Additive Manufacturing Metrology Testbed (AMMT). Knowledge of radiance temperature with a well understood uncertainty budget is a necessary initial step towards an ultimate project goal of traceable emittance and true surface temperature across the heat affected zone, which is a key objective in additive manufacturing research, and the subject of another paper at this conference. Reliable measurements of radiance temperature with an imaging system require (1) calibration of its responsivity at select radiance levels, (2) establishing a calibration equation that interpolates between these levels, (3) dealing with finite spectral bandpass and spatial non-uniformity of the sensor responsivity, and (4) ability for compensate effects of imperfect optical imaging and readout electronics on spatial distribution of the target. The developed system includes an integrating sphere-based calibration source, a pyrometer for its calibration against external blackbody, and an imaging system co-axially aligned with the heating laser, each of which using identical narrow band filters. This paper describes the evaluation of an 850 nm band, with additional wavebands planned for the future. This paper presents experimental results, description of measurement equation and processing algorithm, as well as a framework for establishing an uncertainty budget, including current estimates and future performance goals.

Thermochemical energy storage (TcES) is one of the solutions that use reversible endothermic and exothermic chemical reactions for heat storage and output, respectively. It has several advantages such as a high thermal storage density, and a constant temperature output owing to chemical equilibrium, etc. Recently, carbonation and decarobonation reaction process in Li metal oxide is proposed for use in thermochemical energy storage (TcES) and chemical heat pump (CHP) systems at around 700 °C with the cyclic reaction durability. This system is unique because there is no reported material that can be used for TcES at around 700 °C, even though this is becoming a very important temperature range for heat utilization in solar thermal power plants, high-temperature gas-cooled reactors, and for hydrogen production by fuel reforming. In this study, the method signal imposing visualized a lithium orthosilicate/carbon dioxide (Li4SiO4/CO2) reaction by absolute temperature image transformed from the decoded imposed analog temperature data. The exothermic carbonation, the endothermic solid-liquid phase change, and the endothermic decarbonation are thermally visualized above 700 °C. The analysis of the reaction surface of the carbonateoxide external shell is to be utilized to quantify the lithium diffusion to further form carbonate.

A convolutional neural network (CNN) was developed to recognize sprinkler activation based on long-wave infrared (LWIR) images, creating a nonintrusive, real-time model for detecting sprinkler activation. Training data were taken from ten large-scale fire tests with storage heights ranging between 4.6 m and 13.7 m and ceiling heights ranging between 6.1 m and 15.2 m. A sample of 25,000 LWIR images was extracted from the fire tests, split 70/30 between training/testing data. To prevent overfitting, the images were randomly reversed and cropped. The time required to train the model was reduced by 96% through GPU computing. The overall accuracy of the model was 99.7% for both pendent and upright sprinklers. The methodology described in this study can be generalized and applied to other image classification problems.

There are ongoing economic pressures in production agriculture to increase crop yields. However, high grain yield production comes at a cost of applying significant quantities of various agricultural inputs, i.e. nutrients, pesticides and irrigation. In traditional farming systems, producers attempt to apply these inputs at a uniform rate across a given field. However, due to inherent spatial variability in fields, not all areas may require the same levels of input. Although the spatial and temporal variability of yield limiting factors discussed above has been recognized for a long time (Rennie and Clayton, 1960; Malo and Worcester, 1975; Robert et al., 1990), farmers continued to manage their fields uniformly because they lacked the technology to manage for variability. With the introduction of new precision farming technologies such as global positioning systems (GPS), geographic information systems (GIS), remote sensing, and variable rate application technology (VRT) farmers now have the ability to manage their fields site specifically.

Real time nondestructive evaluation is required for composites load testing. The early detection and measurement of damage progression is important to understand failure modes. A single stringer panel was subjected to quasi-static loading to induce deformation which can result in the formation of delamination damage between the stiffener flange and skin. Passive thermography was used to detect damage in real time as a function of the applied load. The loading was stopped when damage growth was detected. Of particular interest was the early detection of damage formation which can be challenging, as compared to cyclic fatigue loading. Passive thermography data were acquired and processed in real time and revealed damaged areas due to heating from fiber breakage and delamination formation. The processed thermal imagery was also compared to acoustic emission and ultrasound data.

Past analysis of the heat generated during cyclic loading of composites has been primarily focused on the thermal response that occurs at the same frequency as the cyclic load. However, it has been observed that a smaller amplitude signal occurs at twice the frequency of the cyclic load. A physics-based model is presented that describes how this signal is expected as a result of the heat generated by friction at a delamination. The second harmonic source is incorporated into a quadrupole two-dimensional simulation of heat diffusion, which allows for rapid simulation of a temperature profile at the surface from a friction source.

One of the most important advantages of using high-diffusivity alloys like aluminium, in industry, is to reduce the weight without renouncing to high strength components. To accelerate the time of the mechanical characterisation, frequently experimental methods based on temperature measurements are adopted, even if in this case, these methods could involve in wrong estimations. In particular, the study of energy dissipations could produce some assessment errors of fatigue limit due to the fact that the fraction of the detected energy dissipated could be lower if compared to the effective energy intrinsically dissipated in the material due to damage. Furthermore, the fatigue life assessment of Aluminium alloys is problematic due to a non-distinct ‘knee’ in the S-N curve. To take into account these issues and to estimate the fatigue strength in rapid and accurate way, in this work, a method providing a specific thermal signal analysis is presented applied to an aluminium alloy 5754 H-111. Firstly, the well-known methods based on direct temperature measurements for estimating fatigue strength of metals, were applied on an aluminium alloy 5754 H111 in order to demonstrate their problematic application for high-diffusivity materials. Furtherly, a specific thermal signal analysis was adopted for extracting first and second order temperature variations as better parameter for fatigue strength assessment. This work questions the use of direct temperature evaluation in high diffusivity materials and fully replaces it in favor of an approach based on in-depth analysis of thermal signal by using thermoelastic and dissipative temperature variations.

During the fused deposition modeling (FDM) process, heat is exchanged by convection with the surrounding air and by conduction with the platform. Therefore, modeling the thermal behavior of the FDM process requires accurate convective heat transfer coefficient (CHTC) and interfacial conduct resistance (ICR) data. The traditional approach to solving this problem is iterative in nature and requires considerable computation time. In this work, an artificial neural network model was designed and trained using a total of 100 sets of data from a finite element model that reproduces the geometry of the manufactured part. A backpropagation neural network was developed, in which thermal profile characteristics of two specific points were used as input variables while the corresponding CHTC and ICR were selected as the output variables. A correlation coefficient of 0.999 was achieved during training. After training the model, the response of the thermally excited surface was monitored and recorded using an infrared camera and characteristics of the experimental condition were used as inputs to evaluate CHTC and ICR. It was estimated that HTC and ICR equal 61.7 and 2894 W/(m²K) in our experimental model, respectively. The developed models could offer significant advantages when heat transfer coefficients need to be estimated repeatedly.

The United States Army Aviation and Missile Research, Development and Engineering Center (AMRDEC) has utilized Infrared (IR) cameras to analyze boundary layer transition on additively-manufactured and aluminum wings in half-scale wind tunnel testing. The primary goal of the testing was to collect transition data for validation of Computational Fluid Dynamic (CFD) models with traditional oil flow visualization methods. A secondary goal was to collect transition data using IR thermographic imagery. Using non-contact IR cameras allow for more measurements to be collected in a given time. This work focuses on the IR cameras, the testing (setup, results, and lessons learned), and post analysis of the data. Brief descriptions of the test assets and the cameras are given, followed by a description and discussion of strengths and weaknesses of different methods used to accentuate the thermal signature of the transitions. Lining the wing with a selfadhesive liner can increase the contrast of the transition signature passively, but active heating with a central heating element was shown not to be as effective. General lessons learned for test setup, camera selection, and techniques to increase thermal transition signature are provided within each section. By examining several runs, general observations about the airflow transitions are made. Image processing techniques were utilized to analyze the transition. These techniques and resulting toolsets for data analysis are described. Some of the initial results were analyzed to make some comparisons between the traditional oil flow visualization methods and the thermal imaging methods. The report shows that the oil does not affect the repeatability of the thermal signature, but that the transitions determined by the oil flow analysis and the thermal image do differ slightly. Also, the oil flow is able to visualize a region known as the laminar boundary layer separation, whereas, at this time, this phenomenon is still not apparent in the thermal imagery. Further analysis is ongoing to determine if that separation can actually be seen with this specific test configuration.

In this work we apply the finite element (FE) method to simulate the results of pulsed phase thermography experiments on laminated composite plates. Specifically, the goal is to simulate the phase component of reflected thermal waves and therefore verify the calculation of defect depth through the identification of the defect blind frequency. The calculation of phase components requires a higher spatial and temporal resolution than that of the calculation of the reflected temperature. An FE modeling strategy is presented, including the estimation of the defect thermal properties, which in this case is represented as a foam insert impregnated with epoxy resin. A comparison of meshing strategies using tetrahedral and hexahedral elements reveals that temperature errors in the tetrahedral results are amplified in the calculation of phase images and blind frequencies; we investigate the linearity of the measured diffusion length (based on the blind frequency) as a function of defect depth. The simulations demonstrate a nonlinear relationship between the defect depth and diffusion length, calculated from the blind frequency, consistent with previous experimental observations. And finally a two-point strategy is presented to better estimate the defect depth and thickness.

Quartz halogen lamps have highly desirable properties for use in transient thermography including low cost, high power, and low weight. Those properties make them attractive for inexpensive portable systems. On the flip side, halogen lamps have slow turn-on and turn-off times, which can exceed the response time of the tested samples. Their slow response results in inefficient use of power. An additional problem is the large inrush current during turn-on. Considering the intermittent mode of operation – a few seconds on and then a few seconds off, this is a severe limitation. The inrush current can overload the power line and restrict available power. When using the newly introduced equivalent wave field thermography, it is important to know the exact heating profile of the lamp. Methods to extract this profile from the lamp parameters or the thermography data are presented. In this presentation I will introduce a lamp model based on the physics of the filament. The model has an analytical solution during the cooling phase and it was solved numerically during the active heating phase. The model compares very well with the measured data. Using the model, it is possible to analyze electronic lamp drivers and the lamp parameters and their effect on total system performance.

By using relationships between wave propagation and thermal diffusive propagation, it was shown that that one can transform from diffusive propagation into an equivalent wave field. The transformation results in sharp reflections with time delay proportional to the distance. The performance of the transform was tested on carbon composite samples using either xenon flash or incandescent quartz halogen light bulb excitations. The images are as good as any of the common techniques in use. The method can detect artificial damage locate at the depth of the 12^th carbon mats. Application of back projection was also demonstrated. The combined use of the equivalent wave field transform and back projection improves both depth and lateral resolution. The technique is very efficient in term of computational load.

In ancient buildings, knowing the composition and the conservation status of walls is a crucial issue to ensure their durability. The presence of defects or discontinuities could be found using InfraRed Thermography (IRT) with different heating techniques. In order to properly calibrate the thermographic testing procedure, a mock-up wall is studied. The specimen is made of ancient bricks and has defects inside the plaster layer at different depths. Three kinds of heating patterns are delivered on the wall: step, sine wave, and chirp. All the three heating patterns are able to enhance the defect from the sound area after a proper image processing analysis. The differences between each technique are presented with a signal to noise ratio evaluation.

Heavy-duty anticorrosion coating with multiple-layered paints is applied to long-span steel bridge members on the sea. By aging deterioration, the coating is worn from surface year by year. Appropriate repainting programs should be adopted for the maintenance of the bridges according to the evaluation of wear extent. In this study a new nondestructive evaluation technique using short wavelength infrared (SWIR) camera, that enables us to easily detect the wear loss of surface fluororesin coating layer, is developed based on the difference in spectral absorptance between surface fluororesin coating and inner-layer epoxy resin coating.

Inductive thermography is a non-destructive technique, which can be excellently used for detection of surface cracks in electrically conductive materials. In ferro-magnetic steel even a single short pulse with duration of 50ms up to 1s is enough to induce a Joule heating which makes shallow cracks well detectable in the infrared image sequences. In the case of non-magnetic materials with high electrical and thermal conductivity, as e.g. aluminum, the situation is much more difficult: on the one hand a short heating pulse duration is necessary, otherwise the thermal signal diminishes too quickly due to the thermal diffusion. On the other hand with a short heating pulse it is not possible to induce enough heat in the material; therefore the signal-to-noise ratio becomes too low for defect detection. A possibility to overcome this problem is to apply a sequence of short pulses, as it is also done in the lock-in thermography. It is investigated, how many pulses and which pulse duration is necessary to detect surface cracks with different crack depths in non-magnetic materials, as in aluminum. It is also studied, how the heating power, that means the temperature increase during one heating pulse, influences the detectability. Experimental results are presented, obtained for an aluminum sample with artificial cracks and they are compared also with numerical simulations.

Non-Destructive Evaluation (NDE) trials were performed on aramid and ultra-high molecular-weight polyethylene (UHMWPE) based armor systems. Pulsed thermography, continuous heating, and lock-in thermography were investigated for various types of damage. It is shown that the infrared thermography results vary significantly based on the material and thickness of the armor system, and only certain types of damage can be confidently identified. While the pulsed thermography performed in reflection mode was the fastest and provided the strongest indication signal for some types of damage, deeper damage on thicker armor system needed to be performed in transmission mode. Due to inherent material properties variations in these armor systems, the infrared images were affected by non-uniformity. In addition, due to low thermal conductivity, the inspections were sporadically affected by non-uniform heating. Approaches are presented to address the non-uniform heating issue affecting the inspection of those low thermal conductivity materials.

The results of applying three nondestructive testing techniques to the inspection of parts of a new Russian TVS-2DTS airplane made of carbon fiber reinforced plastic are presented. A basic technique implemented in workshop conditions implements optical stimulation of inspected parts. The usefulness of ultrasonic infrared thermography combined with laser vibrometry in the evaluation of parts with complicated geometry is illustrated. Samples with artificial and real defects have been tested in workshop conditions.

In this paper, a novel optical air-coupled ultrasound (O-ACU) technique is proposed. A wide broadband (100 KHz - 1 MHz) laser-acoustic based optical microphone worked as probe in an air-coupled ultrasound (ACU) system. The O-ACU modality was used to detect several CFRP and GFRP impacted laminates and the results were compared with the classical ACU modality. Infrared thermography, as an established reference technique, was used for the validation. Advanced image processing techniques were applied. Conclusively, O-ACU shows an obvious improvement in sensibility and resolution.

Aluminium alloys present some criticalities in terms of fatigue life characterisation due to the absence of a point representing the ‘fatigue limit’, the topic becomes complicated when the material is welded. In this case, the fatigue characterisation lies on design specifications which have to clearly explain the guidelines for the performing the tests and for evaluating the failures, in order to design tailored welded joints. However, the fatigue of welded joints is a difficult subject since the welding process makes the material different, introducing residual tensions, defect, etc. Also, the standard test methods provide only the estimation of the strength at fixed loading cycles but no information on the damage processes occurring in the material. Prompted by these issues researchers deal with the study of other approaches to achieve not only information on fatigue resistance but also damage information. In particular, the thermography can be used for thermal signal analysis of dissipative heat sources involved in fatigue of material undergoing cyclic test. In this paper, this approach is adopted to study the fatigue behavior of friction stir welded joints of AA5754-H111 during specific loading conditions. The component of the temperature related to intrinsic dissipations is assessed and the fatigue strength is evaluated together with a graphical study of the location of damaged areas.

The Friction Stir Welding (FSW) is an innovative solid-state welding method based on frictional and stirring phenomena, discovered and patented by TWI Ltd in 1991, providing high quality components for aerospace, marine and automotive industrial fields. In this process, a rotating non-consumable tool that plunges into the work piece and moves forward produces the heat necessary to weld the parts together. The much lower temperatures compared with those achieved in traditional welding processes by melting, determine the following main advantages of FSW: minimal mechanical distortion, excellent surface finish, absence of splash, no crack formation and porosity after welding, thanks to the low input of total heat. This work deals with the use of thermographic techniques for monitoring the friction stir welding process applied on AA 5754-H111 plates, in order to evaluate the quality of the produced joints in terms of presence of defects and Mechanical strength. The adopted experimental approach was addressed to study and optimizing the FSW process by analyzing the thermographic sequences and extracting several indexes related to the heating involved in the process. Such the indexes, the maximum temperature, the heating and cooling rate of the material, correlated to the frictional power input and the presence of defects respectively, have been investigated for different process parameters (the travel and rotation tool speeds) configurations. The results of the research have been quantitatively supported and characterized by destructive and non-destructive techniques.

This paper deals with the use of eddy current thermography for spot weld nugget diameter assessment. As a nondestructive testing method, eddy current thermography is successfully used to give an estimation of the nugget diameter of resistance spot weld. A ferrite-yoke based inductive coil is used to thermally heat-up spot welds while monitoring the opposite face of the heated face using infrared camera with 40µm/pixel spatial resolution. The inductive coil and the camera are placed at different side of the sample. The heat wave travels from one side to the other through areas with different thermal properties. The recorded thermal response is processed using Fourier transformation which allows identifying non-destructively the nugget and the heat affected zone. The nugget diameter is estimated in pixel and the camera resolution is used to retrieve the value in millimeters. The results, compared with destructive micrographic cut as a reference, are in good agreement.

The first Thermosense Conference held at the Chattanooga Choo-Choo Hotel in 1978 was in response to the “Carter Energy Crisis”. There were three sessions with a total of fifteen papers presented. The sessions all dealt with IR thermography with the first devoted to building heat loss, the second giving case studies and the third devoted to progress, pitfalls and potentials. There was also a poster session. Thermosense was sponsored initially by eight organizations. SPIE now sponsors Thermosense.

The conference was dubbed “Thermosense” by one of the founders, Tom Lillesand, who, along with the other two founders, Alan Stevens and Bob Madding, organized and chaired the conference. About 200 people attended Thermosense I. Initially, Thermosense was completely focused on energy conservation in buildings. As IR technology evolved, applications were developed in numerous different areas. The current focus of IR thermography applications at Thermosense is primarily in the areas of maintenance diagnostics, building science, research and development, non-destructive testing and manufacturing processes. The application of IR thermography technology has also evolved with sophisticated data analysis systems and data acquisition systems, e.g. drones. Plus, more applications are being automated. The user base has expanded tremendously as the technology evolves making IR cameras easier to use and less costly.

One of urgent security problems is a detection of objects hidden on a human body. Obviously, for safety reasons, X-rays cannot be used for such object detection widely and often. For this purpose, the passive THz camera is used with high efficiency. However, IR camera is much cheaper in comparison with the passive THz camera cost. Therefore, using the IR camera for the detection of objects hidden on the human body under clothes is more preferable. We examine applicability for this aim the IR camera, produced by FLIR Company.

For increasing of image quality we propose changing the temperature mode in a room where the detection of an object is provided. Using the temperature contrast between various rooms, in which sequentially a person is, one can essentially enhance the observability of an object hidden under clothes during about 5 minutes time interval, at least. We show that it is possible to see banknote (and other objects) concealed on the human body. It means enhancing many times of temperature resolution of IR camera.

It is well established that diabetes is linked with changes in ocular hemodynamics and retinal microaneurysms. However, it is difficult to diagnose a microaneurysm in a retinal vascular network using a traditional eye exam. The hypothesis of this study is that an overflow in the retinal vascular network will result in a temperature increase, and a microaneurysm could create a local hot spot. Therefore, this work investigates the possibility of applying infrared thermography to detect abnormal blood flow. As a precursor to human or animal testing, an electrical resistance network was used to simulate blood flow (using an electrical circuit analogy). An electrical signal with varied frequencies and peak voltages was used as the heating source. An infrared camera was used to acquire thermography images from the electrical resistance network. Thermal characteristics of the network were able to be derived from the images, suggesting that a timedependent and spatially resolved temperature mapping can be obtained and quantitatively analyzed. Moreover, combined with numerical simulation, the effect of blood flow change on surface temperature variation was investigated. This approach provides a way to apply thermal infrared imaging in diagnosis of retinal vascular diseases.

The certification procedure for building thermographers in Finland was launched 2003. After 14 years training courses the interpretation and reporting procedures have been renewed and modernized, also the new requirements have been now accepted for building thermographers. The normal procedure of building thermography is two-stage thermography in connection of air-tightness test and now first time there was a pilot course combining the air-tightness and building thermography certification. In this presentation some updated requirements for building thermographers are introduced, also typical deficiencies and errors what the thermographers do.

Because European Union`s Energy Performance of Buildings Directive came into the force in the member states, it caused lot of changes in Building Codes in Finland, and now the role of building codes will be changed, too. This has caused the generalization of building thermography during the last 10-15 years, and this development also raised the certification of building thermographers.

Aerial thermography using drones has grown rapidly. Other wavelengths can be combined with thermography, like hyperspectral imaging and of course normal visual imaging. There are no guidelines dealing with the use of drones and aerial thermography for various applications. This paper also briefly discusses the challenges of drones based on Finnish experiences.

In-line mixing technologies used in paper and pulp manufacturing have been studied long and broadly by XAMK Fiberlaboratory in Savonlinna, Finland. Especially, wider introduction and diversification of technologies related to mixing of paper chemicals have created a need to determined research of the in-line mixing technologies. In Finnish research project FLASH, a ground was based for researching and developing the fast in-line mixing techniques together with companies operating in pulp and paper industry segment. Application potential, basic knowledge, measurement technologies, experiment techniques, and research facilities were surveyed for utilizing them later in practical processes. One of the tested measurement technologies was high-speed infrared imaging.

The high-speed infrared imaging tests were carried out together by VTT, XAMK and the companies in Fiberlaboratory research facility in 2013-2015. The Fiberlaboratory research facility includes medium-consistency pulp (MC) chemical mixing equipment, which is almost equal to real life paper mill chemical mixing environment. The infrared imaging was done with the help of IR transmitting sapphire window attached to suitable point in mixing tube system. Temperature differences of main flow and mixing flow enabled analyzing and calculating mixing indexes for different mixing drive parameters successfully.

VTT has also designed a new kind of infrared omnilens for example for panoramic streetview thermography. The VTT omnilens technology enables the streetview thermography with a single infrared camera. Horizontal 360 degree infrared image is achieved by novel lens solution and also vertical image portion is possible. The streetview thermography is useful when finding thermal leaks from buildings in wide area or it can be used to find thermal leaks inside buildings with wheeled small vehicles. Also, utilizing the omnilens in drones to prevent them to collide each other or other drone applications are possible in the future.