This PDF file contains the front matter associated with SPIE Proceedings Volume 7661, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

Infrared imaging has proven to be an invaluable tool for remotely detecting and tracking coupled near-surface thermalhydrodynamic structures such as foam patches of breaking waves, Langmuir circulation and convective cells, thermal impressions of water mass movement and pollutant effluxes. The ability to quantify such characteristics is vital to determining the complex nature of heat transport, gas entrainment and momentum exchange across air-water interfaces. These physical processes play an important role in determining global climate and their accurate description is necessary for consistent weather modeling. In this presentation, we focus on a laboratory scale subsurface turbulent water jet that serves as a canonical near surface event. The jet liquid has a slightly elevated temperature and is placed in close proximity to the air-water interface of a quiescent water basin into which it flows. Infrared image sequences of the surface thermal field were collected for various water jet flow rates and used to examine the detailed statistical nature of the resulting coupled thermal-hydrodynamic field. We discuss the similarities of the spatial structure of the surface thermal field in light of observations made with other sensing techniques, the relevant length and thermal scales present and the order of the fluctuating surface thermal field using Karhunen-Loeve analysis.

The Rochester Institute of Technology (RIT) collected visible, SWIR, MWIR and LWIR imagery of the Midland (Michigan) Cogeneration Ventures Plant from aircraft during the winter of 2008 - 2009. RIT also made ground-based measurements of lake water and ice temperatures, ice thickness and atmospheric variables. The Savannah River National Laboratory (SRNL) used the data collected by RIT and a 3-D hydrodynamic code to simulate the Midland cooling lake. The hydrodynamic code was able to reproduce the time distribution of ice coverage on the lake during the entire winter. The simulations and data show that the amount of ice coverage is almost linearly proportional to the rate at which heat is injected into the lake (Q). Very rapid melting of ice occurs when strong winds accelerate the movement of warm water underneath the ice. A snow layer on top of the ice acts as an insulator and decreases the rate of heat loss from the water below the ice to the atmosphere above. The simulated ice cover on the lake was not highly sensitive to the thickness of the snow layer. The simplicity of the relationship between ice cover and Q and the weak responses of ice cover to snow depth over the ice are probably attributable to the negative feedback loop that exists between ice cover and heat loss to the atmosphere.

The ALGE code is a hydrodynamic model developed by Savannah River National Laboratory (SRNL) to derive the power output levels of an electric generation facility from observing the associated cooling pond with an aerial imaging platform. Over the past two years work has been completed to extend the capabilities of the model to incorporate snow and ice as possible phenomena in the modeled environment. In order to validate the extension of the model, intensive ground truth data as well as high-resolution aerial infrared imagery were collected during the winters of 2008-2009 and 2009-2010, for a combined eight months of data collection. Due to the harsh and extreme environmental conditions automatic data collection instruments were designed and deployed. Based on experience gained during the first collection season and equipment design failures, overhauls in the design and operation of the automated data collection buoys were performed. In addition, a more thorough and robust twofold calibration technique was implemented within the aerial imaging chain to assess the accuracy of the retrieved surface temperatures. By design, the calibration method employed in this application uses ground collected, geolocated water surface temperatures and in-flight blackbody imagery to produce accurate temperature maps of the pond in interest. A sensitivity analysis was implemented within the data reduction technique to produce accurate sensor reaching temperature values using designed equipment and methods for temperature retrieval at the water's surface.

An alternative model to determine the wind influence from themographic inspections is addressed in this paper. A wind velocity dependent temperature reduction factor is developed and applied in order to estimate the target temperature in the absence of wind. The model makes use of only two unknown coefficients, which are identified for each case. Tests were conducted in laboratory using an aclimatiezed chamber developed to simulate actual conditions, as well in the field. The results of application were also compared to those obtained from other researchers, showing very good agreement.

Face recognition is an area of computer vision that has attracted a lot of interest from the research community. A growing demand for robust face recognition software in security applications has driven the development of interesting approaches in this field. A large quantity of research in face recognition deals with visible face images. In the visible spectrum the illumination and face expressions changes represent a significant challenge for the recognition system. To avoid these problems, researchers proposed recently the use of 3D and infrared imaging for face recognition. In this work, we introduce a new framework for infrared face recognition using texture descriptors. This framework exploits linear and non linear dimensionality reduction techniques for face learning and recognition in the texture space. Active and passive infrared imaging modalities are used and comparison with visible face recognition is performed. Two multispectral face recognition databases were used in our experiments: Equinox Database (Visible, SWIR, MWIR, LWIR) and Laval University Multispectral Database (Visible, NIR, MWIR, LWIR). The obtained results show high increase in recognition performance when texture descriptors like LBP (Local Binary Pattern) and LTP (Local Ternary Pattern) are used. The best result was obtained in the short wave infrared spectrum (SWIR) using non linear dimensionality reduction techniques.

Hand-held thermal imaging systems are an important tool for fire and rescue services conducting search and rescue tasks. However, in order to achieve wide-spread deployment the cost of such systems must be minimised, and this generally leads to reduced image quality. Within this paper the use of advanced image processing functions to increase the imaging system performance is discussed. Of particular note is the use and benefits of noise reduction and contrast enhancement. Results from a developed camera system are presented, and the performance gains are illustrated and discussed.

The Panoramic Area Surveillance System (PASS) provides a unique imaging and processing capability for a wide range of security and situational awareness applications. PASS comprises a network of multi-modal cameras and its operational performance is derived from a range of extensive image and data processing functions implemented as realtime software on commercially available hardware. The development of PASS has offered a number of design challenges, including the balance between implementation constraints and system performance. Within this paper, the PASS system and its development challenges are described and its operation is illustrated through a range of application examples.

Open steel grids are typically used on bridges to minimize the weight of the bridge deck and wearing surface. These grids, however, require frequent maintenance and exhibit other durability concerns related to fatigue cracking and corrosion. Bridge decks constructed from composite materials, such as a Fiber-reinforced Polymer (FRP), are strong and lightweight; they also offer improved rideability, reduced noise levels, less maintenance, and are relatively easy to install compared to steel grids. This research is aimed at developing an inspection protocol for FRP bridge decks using Infrared thermography. The finite element method was used to simulate the heat transfer process and determine optimal heating and data acquisition parameters that will be used to inspect FRP bridge decks in the field. It was demonstrated that thermal imaging could successfully identify features of the FRP bridge deck to depths of 1.7 cm using a phase analysis process.

A new remote nondestructive inspection technique, based on thermoelastic temperature measurement by infrared thermography was developed for evaluation of fatigue cracks propagated from welded joints in steel bridges. Fatigue cracks were detected from localized high thermoelastic temperature change observed at crack tips due to stress singularity under variable loading by traffics on the bridge. Self-reference lock-in data processing technique was developed for improvement of signal/noise ratio of the thermal images in the crack detection process. The technique makes it possible to perform correlation processing without an external reference signal under the random loading. In this paper, remote and nondestructive crack detections by the self-reference lock-in thermography were performed for fatigue cracks in actual steel bridge in service. Accuracy improvement of self-reference lock-in thermography method was made by motion compensation technique based on the two-dimensional SSD (Square Sum of Differences) parabola fitting method.

Infrared thermography method is an effective technique for NDT of concrete structure. This paper describes the determination of delamination depths in concrete structure using passive infrared thermography. The sequential thermography data on the surface of concrete specimen are measured by infrared thermography with microbolometer detector, and the solar energy is measured by pyrheliometer in all day. FEM analyses are carried out to calculate the transient temperature on the concrete under the given weather and solar radiation conditions. Based on the results of inverse analysis, in which computed temperature data were compared with experimental data, delamination depth was quantitatively determined.

In this work, different mosaics covered with various plasters (of thickness and compositions) were evaluated in lab by means of active long wave and mid wave thermography approaches, with the intention of detecting the tesserae beneath the plastered surface. Thermal images as well as thermal contrast curves between plastered surfaces and plastered mosaics were recorded. Special considerations concerning the applicability and accuracy of the used approaches for this specific application are presented. Results from the assessment are presented and discussed, indicating that images seeing through the mortar-plaster on plastered mosaic surfaces can be obtained using active thermography approaches.

A device to measure thermal conductivity of small specimens is presented. The specimen is sandwiched between two thermoelectric cells, one sources heat the other sink it. An infrared camera looks at the device and specimen on its side, determining both the heat flux flowing through it and the temperature gradient due to the unknown thermal resistance. The thermal conductivity is quickly recovered, as soon as the steady thermal regime is reached. The heat flux toward the environment is evaluated and minimized working at zero mean temperature difference. A couple of specimens made of materials used to prepare radiant heating floor screeds are measured. The Maxwell model to determine the thermal conductivity of mixture, based on the knowledge of the conductivity of the different phases and their volume fraction, is used to interpret the results.

IR thermography applied in a proper way is able to detect very accurately temperature difference between air and surfaces. By means of this tool is now possible to analyse the local instantaneous heat flux through the surface of a building. In case of steady thermal state, this gives the thermal performance evaluation of the building envelope. In case of a transient condition an averaging process or a system identification algorithm must be applied on time-series of such a data. In any case, it is demonstrated that a standard technique based on thermal flux meter for the thermal resistance (R-value) measurements is more affected by errors than thermographic measurements using this new approach. The method is illustrated with experimental results obtained into a residential building. A dedicated thermographic apparatus is used to map the temperature of the indoor surface of an internal wall and to measure in same positions the air temperature at 10 cm from the surface. From these data the local heat flux is detected at any point of the internal surface. A conventional thermogram of the corresponding outside surface or the outdoor air temperature history allows an easy way to achieve both thermal conductance and transmittance of the investigated wall. In this way it is possible the evaluation of both radiative and convective heat flux on a local basis with a space resolution of 1 cm. The results are here presented within a comparison with the local measurement with a thermal flux-meter device. These results are important in order to enhance energy efficiency and comfort in buildings.

High-resolution, calibrated, near-infrared imagery of the Space Shuttle during reentry has been obtained by a US Navy NP-3D Orion aircraft as part of NASA's HYTHIRM (Hypersonic Thermodynamic InfraRed Measurements) project. The long-range optical sensor package is called Cast Glance. Three sets of imagery have been processed thus far: 1) STS- 119 when Shuttle Discovery was at 52 km away at Mach 8.4, 2) STS-125 when Shuttle Atlantis was 71 km away at Mach 14.3, and 3) STS-128 when Shuttle Discovery was at 80 km away at Mach 14.7. The challenges presented in processing a manually-tracked high-angular rate, air-to-air image data collection include management of significant frame-to-frame motions, motion-induced blurring, changing orientations and ranges, daylight conditions, and sky backgrounds (including some cirrus clouds). This paper describes processing the imagery to estimate Shuttle surface temperatures. Our goal is to reduce the detrimental effects due to motions (sensor and Shuttle), vibration, and atmospherics for image quality improvement, without compromising the quantitative integrity of the data, especially local intensity variations. Our approach is to select and utilize only the highest quality images, register many cotemporal image frames to a single image frame, and then add the registered frames to improve image quality and reduce noise. These registered and averaged intensity images are converted to temperatures on the Shuttle's windward surface using a series of steps starting with preflight calibration data. Comparisons with thermocouples at different points along the space Shuttle and between the three reentries will be shown.

Process models, including finite element modeling simulations, are important for optimizing the metal cutting process, allowing industry to make parts faster, better, and at less cost. Measurements of the process can be used to improve and verify the accuracy of these models. There are many error sources when using infrared radiation thermography to measure the temperature distribution of the tool, workpiece, and chip during metal cutting. Furthermore, metal cutting presents unique measurement challenges due to factors such as the high magnification required, high surface speeds, micro-blackbody effects, and changing emissivity as chips form. As part of an ongoing effort to improve our understanding of uncertainties associated with these thermographic measurements, two sets of experiments were performed. One set explored how well the surface temperature of the cutting tool accurately reflects the internal temperature. This was accomplished by simultaneously measuring the temperature using both a thermal camera and a thermocouple embedded within the cutting tool. The other set investigated correcting for motion blur, point spread function, and a less than ideal range of sensitivity of the thermal camera when measuring the shear zone temperature of the chip. In theory, this correction could be performed using deconvolution. Unfortunately, deconvolutions are sensitive to noise and it is difficult to gauge the uncertainty of the computed values. Thus, convolutions of various assumed inputs were computed and compared to the measured temperatures. Assumed inputs which yielded a good fit to the measured temperatures were considered candidate values. The range of those candidate values yields a measure of the uncertainty of the calculation.

Uncooled thermal cameras using microbolometer focal plane arrays may be used in the long wave infrared (LWIR) for the optical detection of hydrocarbon gas leaks. The strong absorption of hydrocarbon gases in the LWIR may be used to advantage along with the LWIR optical transmission window of the atmosphere. Improvements in the detection algorithm and more robust electronic hardware have produced a gas imager that is well adapted to the detection of large hydrocarbon leaks. The new imaging system relies on a single set of filters to identify a growing list of gases, up to four of them simultaneously. The new detection algorithm reduces the incidence of false alarms by masking portions of the field of view. Because of the camera's long detection range (2 km) and wide field of view, the system is particularly suitable for the supervision of large industrial zones. Results from a field test of leaking gas at a refinery and natural gas processing facility are presented.

As thermal imaging becomes a more accepted technology in industrial environments it can provide exciting new solutions to applications that have been previously dominated by single point pyrometers. The new development of an uncooled focal plane array thermal imager with a narrow band 3.9μm filter and background compensation processing enables measurements in industrial furnaces to provide temperature profiling of the product. This paper will show why the use of a 3.9μm camera with a borescope optic is the most accurate noncontact method for in-furnace temperature measurement. This will be done using the example of a reheat furnace where in a controlled trial using an instrumented billet the measurement from the IR device was shown to accurately track the thermocouple temperature during a variety of furnace operating conditions.

Active thermography has been extensively investigated in the past few years for the nondestructive evaluation of different types of materials. Composites in particular have received considerable attention given that active thermography has shown to be well suited for the detection and characterization of most kinds of defects typically found in these materials such as impact damage, delaminations, disbonds and inclusions. Signal processing is a necessary step of the inspection process, especially if defect characterization is required. A wide variety of techniques have been developed from the classical thermal-based techniques to signal transformation algorithms (adapted from the area of machine vision) on which temporal data is transformed to a different domain (frequency, Hough, principal components, Laplace, high-order moments, etc.) with the purpose of simplifying data analysis. In this paper, a review of some of these processing techniques is presented and exemplified using a Kevlar® panel and a GLARE specimen.

Smart methods for assessing the integrity of a composite structure are essential to both reduce manufacturing costs and out of service time of the structure due to maintenance. Nowadays, thermal non-destructive testing (NDT) is commonly used for assessing composites. This research work evaluates the potential of various infrared thermography (IRT) approaches for assessing different types of fabricated defects (i.e. impact damage, inclusions for delaminations, etc) on Glass Fibre Reinforced Polymer (GFRP) and Carbon Fibre Reinforced Polymer (CFRP) plates. Measurements were performed using LWIR and three active approaches: a) pulsed thermography using the flash method (xenon flash lamps), b) transient themography using IR-heating pulse, and c) thermographic inspection for cooled sample by freezing in -20 °C and then use monitoring. Furthermore, integrated flash thermography by employing a MWIR system was also used.

Advanced ceramic materials are increasingly employed in varied and new applications where improved electrical, mechanical and/or thermal properties are sought. For instance, in a manner similar to carbon or glass fiber reinforced plastics, ceramic matrix composites (CMCs) are designed to improve the naturally brittle characteristics of monolithic ceramics thanks to the inclusion of fibers. Among the main interests for advanced ceramics are the increase in the operation temperature of components, the elimination of the use of cooling fluids, and weight savings. In this paper, the capabilities of infrared thermography and holographic interferometry are investigated and compared for the nondestructive assessment of advanced ceramic materials using three experimental specimens: (1) a monolithic green ceramic tile with fabricated defects, (2) a CMC specimen (from production reject) with a porous alumina matrix reinforced with glass fibers, and (3) a sandwich structure consisting on a carbon fiber honeycomb core with a ceramic plate bonded in one side.

We report on the application of two-dimensional micro-scale thermal analysis with a high-speed infrared (IR) camera equipped with an originally designed optics for the optimum wavelength 3 - 5 micron in order to observe the exothermic latent heat and thermal diffusion during the phase transitions of organic molecular crystals (n-alkanes; n- pentacosane, ntetracosane, and n- tricosane) and polymeric spherulites of poly(ethylene oxide) (PEO). The forerunning phenomenon of phase transition was visualized as the spatial temperature fluctuation by a two-dimensional differential calculus. The exothermic heat patterns of the lamellae growth of n- alkanes and that of spherulites in the radial direction of PEO were observed.

This paper investigates an active thermography approach to probing hidden solder joint geometry. Ten boards were fabricated with the same number of solder joints and amount of solder paste (0.061 g), but using three solder joint geometries (60°, 90°, and 120°). The 90° angle solder pin represented a normal joint, and the 60° and 120° angle pins represented abnormal solder joints. Each board was covered with another board that had three openings just big enough to allow the pin terminals to protrude. A semi-automated system was built to heat and then transfer each board set to a chamber where an infrared camera was used to scan the board as it was cooling down. Each board set underwent the heating, cooling, and scanning process for five trials. Two-thirds of the data set was used for model development and one-third for model evaluation. An artificial neural network (ANN) was constructed to predict abnormal joints given thermal data. Results suggest that solder joints with more surface area cool much faster than those with less surface area. A Finite Element Analysis (FEA) of the heating up and cooling down process consistently predicted solder geometry using the ANN with 86% accuracy. This approach can be used not only to inspect bad solder joints (i.e., low reliability) but also to mass screen for cold solder joints during BGA assembly, since the air gaps in cold solder joints may cause them to cool more slowly than normal joints.

There are commercially available industrial systems for identifying and separating polymers, for instance PE from PP. However, there is a demand for analyzers that can separate within polymer classes: e.g. PE-LD from PE-HD or different polypropylenes characterised by different melting points. First, the feasibility of a reliable spectral identification was tested by extracting different PE and PP samples from an industrial recycling process, and acquiring diffuse reflectance NIR spectra using an FTIR spectrometer. The resulting spectra were then subjected to a chemometrics analysis. We successfully identified characteristic spectral features; these are determined by the chemical bonds of the material, and can be correlated to the melting points of the materials. These features were then adapted for use on a NIR hyper-spectral (HS) system, making it possible to distinguish not only different polymers, but also different types of one polymer in real-time.