This PDF file contains the front matter associated with SPIE Proceedings Volume 9861, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

Researchers at NASA Langley Research Center have been developing the Electron Beam Freeform Fabrication (EBF³) metal additive manufacturing process for the past 15 years. In this process, an electron beam is used as a heat source to create a small molten pool on a substrate into which wire is fed. The electron beam and wire feed assembly are translated with respect to the substrate to follow a predetermined tool path. This process is repeated in a layer-wise fashion to fabricate metal structural components. In-process imaging has been integrated into the EBF³ system using a near-infrared (NIR) camera. The images are processed to provide thermal and spatial measurements that have been incorporated into a closed-loop control system to maintain consistent thermal conditions throughout the build. Other information in the thermal images is being used to assess quality in real time by detecting flaws in prior layers of the deposit. NIR camera incorporation into the system has improved the consistency of the deposited material and provides the potential for real-time flaw detection which, ultimately, could lead to the manufacture of better, more reliable components using this additive manufacturing process.

A 4-color imaging pyrometer was developed to investigate the thermal behavior of laser-based metal processes, specifically laser welding and laser additive manufacturing of stainless steel. The new instrument, coined a 2x pyrometer, consists of four, high-sensitivity silicon CMOS cameras configured as two independent 2-color pyrometers combined in a common hardware assembly. This coupling of pyrometers permitted low and high temperature regions to be targeted within the silicon response curve, thereby broadening the useable temperature range of the instrument. Also, by utilizing the high dynamic range features of the CMOS cameras, the response gap between the two wavelength bands can be bridged. Together these hardware and software enhancements are predicted to expand the real-time (60 fps) temperature response of the 2x pyrometer from 600 °C to 3500 °C. Initial results from a calibrated tungsten lamp confirm this increased response, thus making it attractive for measuring absolute temperatures of steel forming processes.

Laser powder bed fusion (LPBF) is an additive manufacturing (AM) process in which a high power laser melts metal powder layers into complex, three-dimensional shapes. LPBF parts are known to exhibit relatively high residual stresses, anisotropic microstructure, and a variety of defects. To mitigate these issues, in-situ measurements of the melt-pool phenomena may illustrate relationships between part quality and process signatures. However, phenomena such as spatter, plume formation, laser modulation, and melt-pool oscillations may require data acquisition rates exceeding 10 kHz. This hinders use of relatively data-intensive, streaming imaging sensors in a real-time monitoring and feedback control system. Single-point sensors such as photodiodes provide the temporal bandwidth to capture process signatures, while providing little spatial information.

This paper presents results from experiments conducted on a commercial LPBF machine which incorporated synchronized, in-situ acquisition of a thermal camera, high-speed visible camera, photodiode, and laser modulation signal during fabrication of a nickel alloy 625 AM part with an overhang geometry. Data from the thermal camera provides temperature information, the visible camera provides observation of spatter, and the photodiode signal provides high temporal bandwidth relative brightness stemming from the melt pool region. In addition, joint-time frequency analysis (JTFA) was performed on the photodiode signal. JTFA results indicate what digital filtering and signal processing are required to highlight particular signatures. Image fusion of the synchronized data obtained over multiple build layers allows visual comparison between the photodiode signal and relating phenomena observed in the imaging detectors.

Accurate non-contact temperature measurement is important to optimize manufacturing processes. This applies to both additive (3D printing) and subtractive (material removal by machining) manufacturing. Performing accurate single wavelength thermography suffers numerous challenges. A potential alternative is hyperpixel array hyperspectral imaging. Focusing on metals, this paper discusses issues involved such as unknown or changing emissivity, inaccurate greybody assumptions, motion blur, and size of source effects. The algorithm which converts measured thermal spectra to emissivity and temperature uses a customized multistep non-linear equation solver to determine the best-fit emission curve. Emissivity dependence on wavelength may be assumed uniform or have a relationship typical for metals. The custom software displays residuals for intensity, temperature, and emissivity to gauge the correctness of the greybody assumption. Initial results are shown from a laser powder-bed fusion additive process, as well as a machining process.

In addition, the effects of motion blur are analyzed, which occurs in both additive and subtractive manufacturing processes. In a laser powder-bed fusion additive process, the scanning laser causes the melt pool to move rapidly, causing a motion blur-like effect. In machining, measuring temperature of the rapidly moving chip is a desirable goal to develop and validate simulations of the cutting process. A moving slit target is imaged to characterize how the measured temperature values are affected by motion of a measured target.

High performance mid-wave infrared (IR) cameras are used for in-situ electron beam melt process monitoring and temperature measurements. Since standard factory calibrations are insufficient due to very low transmissions of the leaded glass window required for X-ray absorption, two techniques for temperature calibrations are compared. In-situ measurement of emittance will also be discussed. Ultimately, these imaging systems have the potential for routine use for online quality assurance and feedback control.

Automated Fiber Placement (AFP) systems have been developed to help take advantage of the tailorability of composite structures in aerospace applications. AFP systems allow the repeatable placement of uncured, spool fed, preimpregnated carbon fiber tape (tows) onto substrates in desired thicknesses and orientations. This automated process can incur defects, such as overlapping tow lines, which can severely undermine the structural integrity of the part. Current defect detection and abatement methods are very labor intensive, and still mostly rely on human manual inspection. Proposed is a thermographic in situ inspection technique which monitors tow placement with an on board thermal camera using the preheated substrate as a through transmission heat source. An investigation of the concept is conducted, and preliminary laboratory results are presented. Also included will be a brief overview of other emerging technologies that tackle the same issue.

Rainfed agrosystems are important components of the world’s food production system and account for 65–95% of total agriculture. In contrast to irrigated production systems, relatively little attention has been paid to understanding the hydrological interactions between the components of rainfed agrosystems and their impact on water resources, especially groundwater.

A new model, the Surface Energy Balance Algorithm for Rainfed Agriculture (SEBARA), has been developed to estimate the spatial pattern of evapotranspiration in these agrosystems using satellite images (thermal, infrared and visible spectra). The model was calibrated for two competing land uses (Eucalyptus globules tree plantations and pastures) in adjacent catchments in western Victoria, southeastern Australia. Using measurements from a flux tower in the pasture catchment and adjusted sapflow measurements in the plantation catchment, an estimation accuracy of 95% was achieved.

The tree plantations had higher available net radiation, lower soil heat flux and higher latent heat flux, resulting in 15–20% higher evapotranspirative demand than the pasture, depending upon the age and canopy of plantations. The evapotranspiration rate of plantations declines where groundwater depth is >12m or where shallow groundwater is saline. The shallow root system of the pasture means that it relies solely on soil moisture to meet its water requirements and thus has lower evapotranspiration, which varies according to the pasture species.

Tomatoes are the world's 8^th most valuable agricultural product, valued at $58 billion dollars annually. Nondestructive testing and inspection of tomatoes is challenging and multi-faceted. Optical imaging is used for quality grading and ripeness. Spectral and hyperspectral imaging are used to detect surface detects and cuticle cracks. Infrared thermography has been used to distinguish between different stages of maturity. However, determining the freshness of tomatoes is still an open problem. For this research, infrared thermography was used for freshness prediction. Infrared images were captured at a rate of 1 frame per second during heating (0 to 40 seconds) and cooling (0 to 160 seconds). The absolute temperatures of the acquired images were plotted. Regions with higher temperature differences between fresh and less fresh (rotten within three days) tomatoes of approximately uniform size and shape were used as the input nodes in a three-layer artificial neural network (ANN) model. Two-thirds of the data were used for training and one-third was used for testing. Results suggest that by using infrared imaging data as input to an ANN model, tomato freshness can be predicted with 90% accuracy. T-tests and F-tests were conducted based on absolute temperature over time. The results suggest that there is a mean temperature difference between fresh and less fresh tomatoes (α = 0.05). However, there is no statistical difference in terms of temperature variation, which suggests a water concentration difference.

We present a method to characterize vertical cracks in a fast way using burst vibrothermography. In this technique the sample is excited by ultrasounds and, at the defect, rubbing of the contacting surfaces produces heat that can be detected as a temperature rise at the surface using an infrared camera. In this work, first we present the solution of the direct problem, i.e., the calculation of the surface temperature distribution produced by a vertical heat source representing a crack excited by an ultrasound burst, and we choose the information that will be used to characterize the crack, namely, one thermogram and one timing-graph. Next we address the inverse problem, consisting of finding the heat source distribution that is responsible for the observed surface temperature. This inverse problem is ill-posed, and a naïve inversion process is unstable. We propose to use three penalty terms, based on zero order Tikhonov and Total Variation functionals and the Lasso method, to stabilize the inversion. By inverting synthetic data, we analyze the performance of the algorithm as a function of the depth of the heat source and we study the effect of the burst duration and noise level in the data on the quality of the reconstructions. Finally, we invert experimental data taken in samples containing calibrated heat sources. The results show that it is possible to characterize vertical cracks down to depths of 6 mm in AISI 304 stainless steel.

"Classical" IR ultrasonic thermography is based on applying a relatively powerful ultrasonic stimulation to test objects. Attempting to expand an inspection area by further increasing ultrasonic power may lead to sample damage, particularly, at a stimulation point. The recently proposed low-power resonant ultrasonic vibrothermography method involves an individual approach to the inspection of materials being based on a detailed analysis of vibrations on the sample surface in a wide range of acoustic frequencies. The determination of defect resonance frequencies enables efficient transfer of acoustic wave energy into a defect area and further transformation of this energy into heat due to intensive plastic deformations and internal friction. This paper contains the results of applying low-power ultrasonic IR thermography to detecting impact damage in graphite epoxy composite by using techniques of laser vibrometry and IR thermography.

Passive thermography and acoustic emission data were obtained for improved real time damage detection during fatigue loading. A strong positive correlation was demonstrated between acoustic energy event location and thermal heating, especially if the structure under load was nearing ultimate failure. An image processing routine was developed to map the acoustic emission data onto the thermal imagery. This required removing optical barrel distortion and angular rotation from the thermal data. The acoustic emission data were then mapped onto thermal data, revealing the cluster of acoustic emission event locations around the thermal signatures of interest. By combining both techniques, progression of damage growth is confirmed and areas of failure are identified. This technology provides improved real time inspections of advanced composite structures during fatigue testing.

Infrared Thermography (IRT) is a well-known Non-destructive Testing (NDT) technique. In the last decades, it has been widely applied in several fields including inspection of composite materials (CM), specially the fiber-reinforced polymer matrix ones. Consequently, it is important to develop and improve efficient NDT techniques to inspect and assess the quality of CM parts in order to warranty airworthiness and, at the same time, reduce costs of airline companies. In this paper, active IRT is used to inspect carbon fiber-reinforced polymer (CFRP) at laminate with artificial inserts (built-in sample) placed on different layers prior to the manufacture. Two optical active IRT are used. The first is pulsed thermography (PT) which is the most widely utilized IRT technique. The second is a line-scan thermography (LST) technique: a dynamic technique, which can be employed for the inspection of materials by heating a component, line-by-line, while acquiring a series of thermograms with an infrared camera. It is especially suitable for inspection of large parts as well as complex shaped parts. A computational model developed using COMSOL Multiphysics^® was used in order to simulate the inspections. Sequences obtained from PT and LST were processed using principal component thermography (PCT) for comparison. Results showed that it is possible to detect insertions of different sizes at different depths using both PT and LST IRT techniques.

This paper summarizes some common problems of thermal/infrared nondestructive testing and their possible solutions, including optimization of heat source and infrared imager parameters, suppression of additive and multiplicative noise and the use of inversion expressions for estimating defect parameters.

The correct measurement of the performances of thermoelectric (TE) modules for energy conversion is a mandatory task both for laboratory research and for industries engaged in TE modules development or in their integration into thermoelectric generators. A testing device oriented to the maximum flexibility, based on the heat flow meter method at the cold side of the module has been developed. The system is conceived to test TE modules (single or in cascade) with a footprint up to 60x60 mm², from room temperature up to intermediate temperature. Modules can be tested under vacuum or inert atmosphere. Specifically, the flow meter is made of a block of material, with known thermal conductivity, in contact with the cold side of the thermoelectric module. The heat flow is finally determined by measuring the temperature profile along the heat flow path and that is obtained by IR thermography. IR thermography is also utilized to evaluate the contact resistance between the active thermoelectric elements made of ceramic materials and the ceramic layer working as heat diffuser and mechanical support. Some finite element thermal analyses of the system performed for its design are presented.

In this work the influence of the microstructure at the vicinity of the interface on the fracture behavior of particulate-reinforced aluminum alloy matrix composites (Al/SiCp composites) is studied by using thermographic tools. In particular, infrared thermography was used to monitor the plane crack propagation behavior of the materials. The deformation of solid materials is almost always accompanied by heat release. When the material becomes deformed or is damaged and fractured, a part of the energy necessary to initiate and propagate the damage is transformed in an irreversible way into heat. The thermal camera detects the heat wave, generated by the thermo-mechanical coupling and the intrinsic dissipated energy during mechanical loading of the sample. By using an adapted detector, thermography records the two dimensional "temperature" field as it results from the infrared radiation emitted by the object. The principal advantage of infrared thermography is its noncontact, non-destructive character. This methodology is being applied to characterise the fracture behavior of the particulate composites. Infrared thermography is being used to monitor the plane crack propagation behavior of such materials. Furthermore, an innovative approach to use microscopic measurements using IR microscopic lenses was attempted, in order to enable smaller features (in the micro scale) to be imaged with accuracy and assurance.

The global interest in energy applications activates the advanced study about the molten salts in the usage of fluids in the power cycle, such as for transport and heat storage in solar power facilities. However, the basic properties of molten salts show a general scattering in characterization especially in thermal properties. It is suggested that new studies are required on the measurement of thermal properties of solar salts using recent technologies.

In this study, micro-scale heat transfer and phase change in molten salts are presented using our originally developed device: the micro-bolometer Infrared focal plane arrays (IR FPA) measuring system is a portable type instrument, which is re-designed to measure the thermal phenomena in high temperature up to 700 °C or higher. The superimpose system is newly setup adjusted to the signal processing in high temperature to realize the quantitative thermal imaging, simultaneously. The portable type apparatus for a quantitative micro-scale thermography using a micro-bolometer has been proposed based on an achromatic lens design to capture a micro-scale image in the long-wave infrared, a video signal superimposing for the real time emissivity correction, and a pseudo acceleration of a timeframe.

Combined with the superimpose technique, the micro-scale thermal imaging in high temperature is achieved and the molten flows of the solar salts, sodium nitrate, and potassium nitrate are successfully observed. The solar salt, the mixture of sodium nitrate and potassium nitrate, shows a different shape of exothermic heat front morphology in the lower phase transition (solidification) temperature than the nitrates on cooling. The proposed measuring technique will be utilized to accelerate the screening step to determine the phase diagram and the eutectics of the multiple mixtures of candidate molten salts, which may be used as heat transport medium from the concentrated solar power to a processing plant for thermal energy storage.

A typical infrared (IR) thermographic system intended for active thermal/IR nondestructive testing includes a heat source, an IR imager and a computer. The software ensures acquisition and processing of IR image sequences to result in a binary map of defects or other image which is to be interpreted by a thermographer in order to meet inspection requirements. Typically, hardware developers supply a certain set of technical parameters of their units, such as heater power, imager temperature resolution, acquisition rate and a set of available data processing algorithms. The suggested approach allows optimization of inspection parameters if thermal and optical parameters of test materials are known.

The application of the quadrupole method for simulating thermal responses of delaminations in carbon fiber reinforced epoxy composites materials is presented. The method solves for the flux at the interface containing the delamination. From the interface flux, the temperature at the surface is calculated. While the results presented are for single sided measurements, with ash heating, expansion of the technique to arbitrary temporal flux heating or through transmission measurements is simple. The quadrupole method is shown to have two distinct advantages relative to finite element or finite difference techniques. First, it is straight forward to incorporate arbitrary shaped delaminations into the simulation. Second, the quadrupole method enables calculation of the thermal response at only the times of interest. This, combined with a significant reduction in the number of degrees of freedom for the same simulation quality, results in a reduction of the computation time by at least an order of magnitude. Therefore, it is a more viable technique for model based inversion of thermographic data. Results for simulations of delaminations in composites are presented and compared to measurements and finite element method results.

The non-contact acousto-thermal signature (NCATS) is a nondestructive evaluation technique with potential to detect fatigue in materials such as noisy titanium and polymer matrix composites. The underlying physical mechanisms and properties may be determined by parameter estimation via nonlinear regression. The nonlinear regression analysis formulation, including the underlying models, is discussed. Several models and associated data analyses are given along with the assumptions implicit in the underlying model. The results are anomalous. These anomalous results are evaluated with respect to the accuracy of the implicit assumptions.

Subsurface defects can be detected by flash thermography by evaluating the temperature response at the surface. Many techniques have been developed in the past to localize a defect and also to estimate its depth and size. Two of the most established methods are TSR and PPT, whereby TSR analyzes the data in the time domain, and PPT evaluates the signal in the frequency domain. In order to get the data in the frequency domain, Fourier transformation, especially FFT is used to calculate the phase shift for the different frequencies. The usage of FFT assumes a periodical signal or a temporal signal which is limited in the time. As this is not the case for the temperature signal after a short pulse heating, the transformation to the frequency domain generates some errors. Therefore parameters as sampling frequency and duration of evaluation have to be selected carefully. Even if many publications have been already dealing with this topic, in this paper a new approach is attempted by comparing the temporal behavior as it is handled by the TSR technique with the frequency behavior calculated by PPT. The results are interpreted with the help of simulation models of flat bottom hole samples.

We propose a method for tracking the condition of a composite part using Bayesian filtering of ash thermography data over the lifetime of the part. In this demonstration, composite panels were fabricated; impacted to induce subsurface delaminations; and loaded in compression over multiple time steps, causing the delaminations to grow in size. Flash thermography data was collected between each damage event to serve as a time history of the part. The ash thermography indicated some areas of damage but provided little additional information as to the exact nature or depth of the damage. Computed tomography (CT) data was also collected after each damage event and provided a high resolution volume model of damage that acted as truth. After each cycle, the condition estimate, from the ash thermography data and the Bayesian filter, was compared to 'ground truth'. The Bayesian process builds on the lifetime history of ash thermography scans and can give better estimates of material condition as compared to the most recent scan alone, which is common practice in the aerospace industry. Bayesian inference provides probabilistic estimates of damage condition that are updated as each new set of data becomes available. The method was tested on simulated data and then on an experimental data set.

Anti-reflective coating is widely used on telescopes, eyeglasses and screens to effectively enhance the transmission of light. However, the presence of defects such as bubbles or scratches lowers the usability and functionality of optical film. Optical cameras are often used for coating inspection, but their accuracy relies heavily on the illumination source, camera viewing angles and defect location. This paper describes an active thermography approach that can potentially overcome this issue. Eighteen scratch and bubble defects were located on AR film with dimensions ranging from 0.03mm to 4.4 mm. An infrared camera was used to capture thermal images of those defects over 65 seconds of heating. After the thermal images were acquired, time-domain analysis and space-domain analysis were conducted and k-means clustering methodology was used to highlight the defective area. Results suggest active thermography can be used to detect scratch defects with widths of 0.03mm to 4.40 mm and bubble defects with diameters ranging from 0.08 to 4 mm. For defects with dimensions larger than 0.4 mm, our algorithm can estimate the dimension with less than 15% bias. However, for defects with dimensions less than 0.4mm, the algorithm estimation error ranged from 68% to 900% due to camera resolution limitations. It should be noted that our algorithm can still distinguish a scratch defect with a width of less than one pixel. This study also suggests active thermography can detect scratch and bubble defects regardless of the location of the illumination source.

For more than 40 years thermography has been used for electrical problem detection. In addition, since radiometric infrared cameras can establish apparent surface temperature of the problem, a classification system is often utilized based upon surface temperature, or temperature rise above normal operating temperature or ambient air temperature. This however can be an extremely unreliable classification method for a number of reasons including: emissivity and background energy; a lack of regard for failure modes and stressors; surface temperature variability with load and ambient conditions; temperature gradient from internal source to surface; and the presence of convection, just to name a few. Standards, such as NFPA 70B, try to address some of these issues by having very low threshold temperature limits, but this as well has issues including identifying an over-abundance of non-critical problems for immediate repair. This paper will present a risk assessment process and matrix which classifies electrical problems based upon a variety of factors affecting both probability and consequence of electrical component failure. Inherent in this process will be a discussion of understanding and analysing electrical connection failure modes and failure stressors, as well as consideration of both heat energy flow and stored energy rather than only considering surface temperature as a single point predictor of catastrophic failure.

Long-wave infrared (LWIR) cameras provide the unique ability to see through smoke and condensed water vapor. However, soot generated inside the flame does attenuate the LWIR signal. This work focuses on gas flame attenuation effects of LWIR signals originating from a blackbody. The experimental setup consists of time averaged, laboratory-scale turbulent diffusion flames with heat release rates set at 5 kW, 10 kW, and 15 kW. Propylene and ethylene were used as fuel, providing two different soot yields. A 30 cm by 30 cm blackbody was used with maximum surface temperatures set to 600°C. Both instantaneous and time-averaged blackbody temperature profiles through the flame were measured using a LWIR microbolometer camera (7.5–14 μm). Flame intermittency was quantified by color segmenting visible images. The experiments showed that low blackbody temperatures were significantly affected by the presence of the flame. At 600°C, the effect of flame absorption matches the emitted radiation from the flame itself. Using data obtained at various blackbody temperatures, the flame transmittance was obtained using a Generalized Reduced Gradient optimization method. The transmittance was lower for propylene flames compared to ethylene flames. Ethylene flames were shown to have higher temperatures. Using the values for flame radiance and transmissivity, the total averaged radiance of the flame plus the blackbody could be reproduced with 1% accuracy.

The accurate knowledge of the thermal performance could reduce significantly the impact of buildings on global energy consumption. Infrared thermography is widely recognized as one of the key technologies for building surveys, thanks to its ability to acquire at a glance thermal images of the building envelope. However, a spot measurement could be misleading when the building is under dynamic thermal conditions. In this case data should be acquired for hours or days, depending on the thermal properties of the walls. Long term thermographic monitoring are possible but imply strong challenges from a practical standpoint.

This work investigates the possibilities and limitations of spot thermographic surveys coupled with contact probes, that are able to acquire continuously the thermal signal for days, to investigate the thermal bridges of a building. The goal is the estimation of the reliability and accuracy of the measurement under realistic environmental conditions. Firstly, numerical simulations are performed to determine the reference value of an experimental case. Then a long term thermographic survey is performed and integrated with the contact probe measurement, assessing the feasibility of the method.

Infrared thermography is widely applied to the inspection of building, enabling the identification of thermal anomalies due to the presence of hidden structures, air leakages, and moisture. One of the main advantages of this technique is the possibility to acquire rapidly a temperature map of a surface. However, due to the actual low-resolution of thermal camera and the necessity of scanning surfaces with different orientation, during a building survey it is necessary to take multiple images.

In this work a device based on quantitative infrared thermography, called aIRview, has been applied during building surveys to automatically acquire thermograms with a camera mounted on a robotized pan tilt unit. The goal is to perform a first rapid survey of the building that could give useful information for the successive quantitative thermal investigations. For each data acquisition, the instrument covers a rotational field of view of 360° around the vertical axis and up to 180° around the horizontal one. The obtained images have been processed in order to create a full equirectangular projection of the ambient.

For this reason the images have been integrated into a web visualization tool, working with web panorama viewers such as Google Street View, creating a webpage where it is possible to have a three dimensional virtual visit of the building. The thermographic data are embedded with the visual imaging and with other sensor data, facilitating the understanding of the physical phenomena underlying the temperature distribution.

The certification procedure for building thermographers in Finland was launched 2003, when also was published the first guidelines in interpretation of thermal images and reporting guidelines. After 12 years training courses a need has emerged to complement and modernize the interpretation and reporting, also to update what kind of thermal imagers can be used for various applications. Due to the technical progress, performance of devices has improved and image processing softwares have developed. In this paper the new guidelines are introduced, as well some examples of the most common errors of interpretation. The normal procedure is two-stage thermography in connection of air-tightness test.

This paper reports on a system using a Digital Micromirror Device (DMD) to modulate a near-infrared laser source spatially and temporally. The DMD can produce an arbitrary heat source varying both spatially and temporally over the target. When the thermal response of the target surface is recorded using a thermal imager, this provides new possibilities in subsurface defect detection, partially with regard to features whose orientation does not allow them to be resolved using conventional thermographic inspection techniques. In this respect it is similar to conventional focused spot detection approaches; however, the DMD allows the signal to be frequency/phase multiplexed which provides for simultaneous interrogation over a large area. The parallel nature of the process permits a longer inspection time at each point which has signal-to-noise benefits. Preliminary experiments demonstrating the multiplexing approach are presented using a low-cost thermal imager. A NIR laser is spatially and temporary modulated to generated multiple thermal line sources on the surface of a composite circuit board. The infrared response is demodulated point-by-point at each drive frequency. This permits the thermal response from each line source to be resolved individually. Beyond damage detection the approach also has applications to system identification. Initial limitations due to the test setup are discussed along with future system improvements.

Optical fiber lasers offers the advantage of being relatively compact and efficient. However, the materials such as fluoride and chalcogenide glasses used for their fabrication must be exempt of defects in order to make efficient laser systems. However, most existing quality control techniques are not compatible with chalcogenide fibers because of their limited transparency in the visible spectral range. For this reason, the Université Laval's Centre d'optique, photonique et laser (COPL), in Quebec City, Canada, has developed a novel non-destructive testing (NDT) methodology based on infrared imaging to address this problem. The results show how this simple screening technique eases the selection of high-quality fibers for the design of high-power mid-IR lasers.

In this paper, we present a simple method to analyze the injection efficiency of the photodiode interface circuit under fast shuttering conditions for active Imaging applications. This simple model has been inspired from the companion model for reactive elements largely used in CAD. In this paper, we demonstrate that traditional CTIA photodiode interface is not adequate for active imaging where fast and precise shuttering operation is necessary. Afterwards we present a direct amplification based photodiode interface which can provide an accurate and fast shuttering operation on photodiode. These considerations have been used in NIT's newly developed ROIC and corresponding SWIR sensors both in VGA 15um pitch (NSC1201) and also in QVGA 25um pitch (NSC1401).

Originally designed to make the practical examination on thermography certification1 possible, the device presented in this paper has demonstrated to be a very useful and versatile didactic tool for training centers and educational institutions, it can also be used as a low cost blackbody simulator to verify calibration of radiometers. It is a simple device with several functionalities for studying and for applications on heat transfer and radiometry, among them the interesting ability to thermally simulate the surface of real objects. On that functionality, if the device is seen by a thermographic camera, it reproduces the surface apparent temperatures of the object that it is simulating, at the same time, if it is seen by a naked eye it shows a visible image of that same surface. This functionality makes the practical study in the classroom possible, from different areas such as electrical, mechanical, medical, building, veterinary, etc.

We have developed image processing technologies for resolving issues caused by the inherent UFPA (uncooled focal plane array) sensor characteristics to spread its applications. For example, large time constant of an uncooled IR (infra-red) sensor limits its application field, because motion blur is caused in monitoring the objective moving at high speed. The developed image processing technologies can eliminate the blur and retrieve almost the equivalent image observed in still motion. This image processing is based on the idea that output of the IR sensor is construed as the convolution of radiated IR energy from the objective and impulse response of the IR sensor. With knowledge of the impulse response and moving speed of the objective, the IR energy from the objective can be de-convolved from the observed images. We have successfully retrieved the image without blur using the IR sensor of 15 ms time constant under the conditions in which the objective is moving at the speed of about 10 pixels/60 Hz.

The image processing for reducing FPN (fixed pattern noise) has also been developed. UFPA having the responsivity in the narrow wavelength region, e.g., around 8 μm is appropriate for measuring the surface of glass. However, it suffers from severe FPN due to lower sensitivity compared with 8–13 μm. The developed image processing exploits the images of the shutter itself, and can reduce FPN significantly.

The non-invasive, painless, radiation-free and cost-effective infrared breast thermography (IBT) makes a significant contribution to improving the survival rate of breast cancer patients by early detecting the disease. This paper presents a set of standard breast thermogram acquisition protocols to improve the potentiality and accuracy of infrared breast thermograms in early breast cancer detection. By maintaining all these protocols, an infrared breast thermogram acquisition setup has been established at the Regional Cancer Centre (RCC) of Government Medical College (AGMC), Tripura, India. The acquisition of breast thermogram is followed by the breast thermogram interpretation, for identifying the presence of any abnormality. However, due to the presence of complex vascular patterns, accurate interpretation of breast thermogram is a very challenging task. The bilateral symmetry of the thermal patterns in each breast thermogram is quantitatively computed by statistical feature analysis. A series of statistical features are extracted from a set of 20 thermograms of both healthy and unhealthy subjects. Finally, the extracted features are analyzed for breast abnormality detection. The key contributions made by this paper can be highlighted as — a) the designing of a standard protocol suite for accurate acquisition of breast thermograms, b) creation of a new breast thermogram dataset by maintaining the protocol suite, and c) statistical analysis of the thermograms for abnormality detection. By doing so, this proposed work can minimize the rate of false findings in breast thermograms and thus, it will increase the utilization potentiality of breast thermograms in early breast cancer detection.

Medical Infrared Thermography (MIT) offers a potential non-invasive, non-contact and radiation free imaging modality for assessment of abnormal inflammation having pain in the human body. The assessment of inflammation mainly depends on the emission of heat from the skin surface. Arthritis is a disease of joint damage that generates inflammation in one or more anatomical joints of the body. Osteoarthritis (OA) is the most frequent appearing form of arthritis, and rheumatoid arthritis (RA) is the most threatening form of them. In this study, the inflammatory analysis has been performed on the infrared images of patients suffering from RA and OA. For the analysis, a dataset of 30 bilateral knee thermograms has been captured from the patient of RA and OA by following a thermogram acquisition standard. The thermograms are pre-processed, and areas of interest are extracted for further processing. The investigation of the spread of inflammation is performed along with the statistical analysis of the pre-processed thermograms. The objectives of the study include: i) Generation of a novel thermogram acquisition standard for inflammatory pain disease ii) Analysis of the spread of the inflammation related to RA and OA using K-means clustering. iii) First and second order statistical analysis of pre-processed thermograms. The conclusion reflects that, in most of the cases, RA oriented inflammation affects bilateral knees whereas inflammation related to OA present in the unilateral knee. Also due to the spread of inflammation in OA, contralateral asymmetries are detected through the statistical analysis.

As it is well-known, application of the IR camera for the security problems is very promising way. In previous papers, we demonstrate new possibility of the passive THz camera using for a temperature difference observing on the human skin if this difference is caused by different temperatures inside the body. For proof of validity of our statement we make the similar physical experiment using the IR camera. We show a possility of viewing the temperature trace on a human body skin, caused by temperature changing inside the human body due to water drinking. We use new approach, based on usung a correlation function, for computer processing of IR images. Its application results in a temperature resolution enhancing of cameras.

We analyze IR images of a person, which drinks water. We follow a temperature trace on human body skin, caused by changing of temperature inside the human body. Some experiments were made with measurements of a body temperature covered by shirt. We try to see a human body temperature changing in physical experiments under consideration. Shown phenomena are very important for the detection of forbidden objects, cancelled under clothes or inside the human body, by using non-destructive control without using X-rays.

Hyperspectral imaging has been considerably developed during the recent decades. The application of hyperspectral imagery and infrared thermography, particularly for the automatic identification of minerals from satellite images, has been the subject of several interesting researches. In this study, a method is presented for the automated identification of the mineral grains typically used from satellite imagery and adapted for analyzing collected sample grains in a laboratory environment. For this, an approach involving Sparse Principle Components Analysis (SPCA) based on spectral abundance mapping techniques (i.e. SAM, SID, NormXCorr) is proposed for extraction of the representative spectral features. It develops an approximation of endmember as a reference spectrum process through the highest sparse principle component of the pure mineral grains. Subsequently, the features categorized by kernel Extreme Learning Machine (Kernel- ELM) classify and identify the mineral grains in a supervised manner. Classification is conducted in the binary scenario and the results indicate the dependency to the training spectra.

Computer vision and photogrammetric techniques have been widely applied to digital imagery producing high density 3D point clouds. Using thermal imagery as input, the same techniques can be applied to infrared data to produce point clouds in 3D space, providing surface temperature information. The work presented here is an evaluation of the accuracy of 3D reconstruction of point clouds produced using thermal imagery. An urban scene was imaged over an area at the Naval Postgraduate School, Monterey, CA, viewing from above as with an airborne system. Terrestrial thermal and RGB imagery were collected from a rooftop overlooking the site using a FLIR SC8200 MWIR camera and a Canon T1i DSLR. In order to spatially align each dataset, ground control points were placed throughout the study area using Trimble R10 GNSS receivers operating in RTK mode. Each image dataset is processed to produce a dense point cloud for 3D evaluation.

Stitching is used to reduce dry-core and reinforce T-joint structure. However, it might cause new types of flaws, especially submillimeter flaws. In this paper, new approaches including micro-VT, lock-in micro-LLT and micro-LST based on both lock-in and pulse methods are used to detect submillimeter flaws in stitched CFRP. A comparison of laser excitation thermography and micro-VT on micro-porosities is conducted. Micro-CT is used to validate the infrared results. Then, a finite element analysis (FEA) is performed. The geometrical model needed for finite element discretization was developed from micro-CT measurements. The model is validated for the experimental results. Finally a comprehensive experimental and simulation comparison of micro-LLT and micro-LST based on both lock-in and pulse methods is conducted.

Nondestructive testing (NDT) techniques using pulse heating infrared thermography and terahertz (THz) imaging were developed for detecting deterioration of oil tank floor, such as blister and delamination of corrosion protection coating, or corrosion of the bottom steel plate under coating. Experimental studies were conducted to demonstrate the practicability of developed techniques. It was found that the pulse heating infrared thermography was utilized for effective screening inspection and THz-TDS imaging technique performed well for the detailed inspection of coating deterioration and steel corrosion.

The proposed approach addresses the problem of retrieving the emissivity of hyperspectral data in the spectroscopic imageries from indoor experiments. This methodology was tested on experimental data that have been recorded with hyperspectral images working in visible/near infrared and long-wave infrared bands. The proposed technique provides a framework for computing down-welling spectral radiance applying non-negative matrix factorization (NMF) analysis. It provides the necessary means for the non-uniform correction of active thermographical experiments. The obtained results indicate promising accuracy. In addition, the application of the proposed technique is not limited to non-uniform heating spectroscopy but to uniform spectroscopy as well.