This PDF file contains the front matter associated with SPIE Proceedings Volume 8354, including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

Advanced composite structures are commonly tested under controlled loading. Understanding the initiation and progression of composite damage under load is critical for validating design concepts and structural analysis tools. Thermal nondestructive evaluation (NDE) is used to detect and characterize damage in composite structures during fatigue loading. A difference image processing algorithm is demonstrated to enhance damage detection and characterization by removing thermal variations not associated with defects. In addition, a one-dimensional multilayered thermal model is used to characterize damage. Lastly, the thermography results are compared to other inspections such as non-immersion ultrasonic inspections and computed tomography X-ray.

Water ingress in honeycomb structures is of great concern for the civil and military aerospace industries. Pressure and temperature variations during take-off and landing produce considerable stress on aircraft structures, promoting moisture ingress (by diffusion through fibers or by direct ingress through voids, cracks or unsealed joints) into the core. The presence of water (or other fluids such as kerosene, hydraulic fluid and de-icing agents) in any of its forms (gas vapor, liquid or ice) promotes corrosion, cell breakage, and induce composite layer delaminations and skin disbonds. In this study, testing specimens were produced from unserviceable parts from military aircraft. In order to simulate atmospheric conditions during landing, selected core areas were filled with measured quantities of water and then frozen in a cold chamber. The specimens were then removed from the chamber and monitored for over 20 minutes as they warm up using a cooled high-resolution infrared camera. Results have shown that detection and quantification of water ingress on honeycomb sandwich structures by passive infrared thermography is possible using a HD mid-wave infrared cameras for volumes of water as low as 0.2 ml and from a distance as far as 20 m from the target.

This work deals with the non destructive analysis of different composite parts and structures using Line Scanning Thermography (LST), a non-contact inspection method based in dynamic thermography. The LST technique provides a quick and efficient methodology to scan wide areas rapidly; the technique has been used on the inspection of composite propellers, sandwich panels, motor case tubes and wind turbine blades, among others. In LST a line heat source is used to thermally excite the surface under study while an infrared detector records the transient surface temperature variation of the heated region. Line Scanning Thermography (LST), has successfully been applied to determine the thickness of metallic plates and to assess boiler tube thinning. In this paper the LST protocols developed for the detection of sub-surface defects in different composite materials commonly used in aerospace applications, plates will be presented. In most cases the thermal images acquired using LST will be compared with ultrasonic c-scans. The fundamentals of LST will be discussed, as well as the limitations of this technique for NDT inspection.

Active thermographic studies proved their capabilities for detection of deeper subsurface details with reduced non uniform emissivity problems for defect detection. In this contribution analysis of subsurface anomalies has been carried out by probing a suitable frequency component with sufficient energy. This paper highlights the comparative analysis of different non-stationary thermographic schemes on the basis of probing equal energy to the chosen frequency component used for the analysis of a carbon fiber reinforced plastic (CFRP) sample used in experimentation. Experiments have been carried out to find the detection ability of different excitation schemes and comparisons have been made by taking signal to noise ratio (SNR) of the defects into consideration.

Both theoretical and experimental results obtained by applying active infrared thermography to the inspection of hidden corrosion in 1-10 mm thick steel samples are presented. The emphasis is put on the comparison of heating and data processing techniques.

In recent study, active thermography has reached a high status as an easy and speedy defects inspection method in a NDT field. This paper newly proposes a non-disassembly and non-contact NDT method using the Vibro-Thermography for detecting and evaluating of fatigue cracks at neck parts of the conveyance roll in the steel making plant. In this method, fatigue cracks are detected as localized high temperature areas caused by friction and impact at crack surfaces with an infrared thermography, applying a high-amplitude ultrasonic vibration. In the case of the roll surface is covered with lubricating grease or dust, the crack detectability is shown. Self reference lock-in data processing technique is applied for improvement of signal noise ratio in the crack detection process. This technique makes it possible to perform correlating process without an external reference signal. Time and cost saving inspection method in the neck part of conveyance roll is carried out using this NDT technique.

Reinforced concrete structures (RCS) have potential application in civil engineering and with the advent of nuclear engineering RCS to be capable enough to withstanding a variety of adverse environmental conditions. However, failures/loss of durability of designed structures due to premature reinforcement corrosion of rebar is a major constrain. Growing concern of safety of structure due to pre-mature deterioration has led to a great demand for development of non-destructive and non-contact testing techniques for monitoring and assessing health of RCS. This paper presents an experimental investigation of rebar corrosion by non-stationary thermal wave imaging. Experimental results have been proven, proposed approach is an effective technique for identification of corrosion in rebar in the concrete samples.

Infrared non-destructive testing and evaluation (IRNDT&E) is an emerging approach for materials characterization due to its capability to test wide variety of solid materials such as metals, composites and semiconductors of industrial interest. Further it supports thorough inspection and evaluation by its unique remote and fast and whole field testing capabilities. Wood is one of the most commonly used house hold building material it has both structural and decorative applications. It is used both in natural and processed form like ply wood, veneer, ply-board etc. Defects like knots, worm track, delaminations, glue smear etc. influences its in-service capabilities. Even though various non-destructive methods such as optical, ultrasonic and radiography are commonly used to inspect wooden materials, infrared imaging has its own advantage due to its safe, whole field inspection capabilities. This paper describes the applicability of the transient thermal wave imaging (TWI) method for inspection of ply wood. This paper highlights applicability of transient pulsed thermal imaging approach for finding out the hidden defects. Capability of the proposed method and its defect detection capabilities have been highlighted through experimental results.

This paper discusses the non-destructive evaluation of thick Carbon/Carbon (C/C) composite aircraft brake disks by using transient infrared thermography (IRT) approach. Thermal diffusivity measurement technique was applied to identify the subsurface anomalies in thick C/C brake disks. In addition, finite element analysis (FEA) modeling tool was used to determine the transient thermal response of the C/C disks that were subjected to flash heating. For this, series of finite element models were built and thermal responses with various thermal diffusivities subjected to different heating conditions were investigated. Experiments were conducted to verify the models by using custom built in-house IRT system and commercial turnkey system. The analysis and experimental results showed good correlation between thermal diffusivity value and anomalies within the disk. It was demonstrated that the step-heating transient thermal approach could be effectively applied to obtain the whole field thermal diffusivity value of C/C composites.

This paper presents the test campaign concept and definition and the analysis of the recorded measurements. One of the most important systems in cars and trucks are brakes. The braking temperature on a lining surface can rise above 500°C. This shows how linings requirements are so strict and, what is more, continuously rising. Besides experimental tests, very supportive method for investigating processes which occur on the brake pad linings are numerical analyses. Experimental tests were conducted on the test machine called IL-68. The main component of IL-68 is so called frictional unit, which consists of: rotational head, which convey a shaft torque and where counter samples are placed and translational head, where samples of coatings are placed and pressed against counter samples. Due to the high rotational speeds and thus the rapid changes in temperature field, the infrared camera was used for testing. The paper presents results of analysis registered thermograms during the tests with different conditions. Furthermore, based on this testing machine, the numerical model was developed. In order to avoid resource demanding analyses only the frictional unit (described above) was taken into consideration. Firstly the geometrical model was performed thanks to CAD techniques, which in the next stage was a base for developing the finite element model. Material properties and boundary conditions exactly correspond to experimental tests. Computations were performed using a dynamic LS-Dyna code where heat generation was estimated assuming full (100%) conversion of mechanical work done by friction forces. Paper presents the results of dynamic thermomechanical analysis too and these results were compared with laboratory tests.

High resolution calibrated near infrared (NIR) imagery of the Space Shuttle Orbiter was obtained during hypervelocity atmospheric re-entry of the STS-119, STS-125, STS-128, STS-131, STS-132, STS-133, and STS-134 missions. This data has provided information on the distribution of surface temperature and the state of the airflow over the windward surface of the Orbiter during descent. The thermal imagery complemented data collected with onboard surface thermocouple instrumentation. The spatially resolved global thermal measurements made during the Orbiter's hypersonic re-entry will provide critical flight data for reducing the uncertainty associated with present day ground-to-flight extrapolation techniques and current state-of-the-art empirical boundary-layer transition or turbulent heating prediction methods. Laminar and turbulent flight data is critical for the validation of physics-based, semi-empirical boundary-layer transition prediction methods as well as stimulating the validation of laminar numerical chemistry models and the development of turbulence models supporting NASA's next-generation spacecraft. In this paper we provide details of the NIR imaging system used on both air and land-based imaging assets. The paper will discuss calibrations performed on the NIR imaging systems that permitted conversion of captured radiant intensity (counts) to temperature values. Image processing techniques are presented to analyze the NIR data for vignetting distortion, best resolution, and image sharpness.

Ground-based high-resolution, calibrated, near-infrared (NIR) imagery of the Space Shuttle STS-134 Endeavour during reentry has been obtained as part of NASA's HYTHIRM (Hypersonic Thermodynamic InfraRed Measurements) project. The long-range optical sensor package called MARS (Mobile Aerospace Reconnaissance System) was positioned in advance to acquire and track part of the shuttle re-entry. Imagery was acquired during a few minutes, with the best imagery being processed when the shuttle was at 133 kft at Mach 5.8. This paper describes the processing of the NIR imagery, building upon earlier work from the airborne imagery collections of several prior shuttle missions. Our goal is to calculate the temperature distribution of the shuttle's bottom surface as accurately as possible, considering both random and systematic errors, while maintaining all physical features in the imagery, especially local intensity variations. The processing areas described are: 1) radiometric calibration, 2) improvement of image quality, 3) atmospheric compensation, and 4) conversion to temperature. The computed temperature image will be shown, as well as comparisons with thermocouples at different positions on the shuttle. A discussion of the uncertainties of the temperature estimates using the NIR imagery is also given.

There is a strong interest in diagnosing engine performance problems and maintenance needs using optical techniques instead of expensive, time-consuming mechanical inspection. A Telops Hyper-Cam MWIR imaging Fourier-transform spectrometer collected spectrally-resolved images of jet exhaust from an F109 turbofan engine operating at 53%, 82%, and 88% of maximum RPM. This work attempts to discern what information content about the turbulent jet flow field is revealed in the measured spectra. The spectrum is examined and simulated, a radial and axial temperature mapping of the plume is presented, and a turbulent temporal and spatial analysis method is demonstrated. Spectral simulation of a pixel centered at nozzle exit finds volume mixing fractions of 3.3% H₂O and 2.8% CO₂ and an exhaust temperature of 560K with the engine at 82%. A single, high frequency turbulent feature is mapped and tracked over several frames. Velocity of this feature, based on the 2.86kHz camera frame rate and 0.067cm² per pixel spatial resolution, is approximately 176^m/s and compares favorably with an estimate based on the measured mass flow rate. This effort is a proof of concept and intended to justify qualitative analysis of a more controlled and characterized turbulent source in future work.

This paper presents two methodologies able to map a block of IR thermal and RGB images on 3D models derived from terrestrial laser scanning surveying. Proposed methods stand out from other traditional approaches that are mainly based on the projection of single images through approximate models. The first method is a rigorous photogrammetric orientation through a bundle adjustment integrating both RGB and thermal data. Then, another complementary solution based on the use of a calibrated 'bi-camera' system is illustrated. Both methods allows one to texture building facades (reconstructed with 3D models) with their temperature values. Finally, several products can be extracted and managed in different data processing environments: triangulated models to visualize 3D spatial information and to analyze 3D heating diffusion on the surface; raster datasets (e.g. orthophotos or rectified images) with temperature as radiometric value. Both approaches were tested on different buildings of Politecnico di Milano University, where a restoration project of historical and modern facades is currently work in progress.

Thermal Bridges act as short circuits for energy flow between conditioned interior space and the outside environment. They readily show up in infrared imaging under appropriate conditions. An example of a thermal bridge in a standard building detail and an alternate design are analyzed to predict the energy impact of the bridge and of removing it. The analysis also provides guidance on whether infrared imaging can detect the thermal bridge.

Energy Performance of Buildings Directive came in to the force in Europe couple of years ago and it had an immediate effect on Building Codes in Europe. Finland have changed its building codes since 2007 - the insulation requirements have been tightened and the requirements have been specified. The biggest change is energy efficient calculations and determination of energy efficiency and energy label for buildings. This has caused a boom of new service providers (thermography services, air-tightness measurements and other services like new calculation tools). Thermography is used in verification in performance of buildings. In this presentation some examples of building thermography in walk-through energy audits combined with the results of energy efficiency calculations are presented - also some special problems in buildings of specific use (e.g. an art museum) and use of thermography to solve them.

Grease lubrication of rolling element bearings is one of the most common lubricated scenarios in industry. The exact behavior of greases while equipment is in operation is not well understood. This paper will detail studies that provide insight into the thermal behavior, flow characteristics of the non-newtonian greases, and changes in grease properties in operating rolling-element bearings.

Black liquor is the fuel of Kraft recovery boilers. It is sprayed into the furnace of a recovery boiler through splashplate nozzles. The operation of a recovery boiler is largely influenced by the particle size and particle size distribution of black liquor. When entrained by upwards-flowing flue gas flow, small droplet particles may form carry-over and cause the fouling of heat transfer surfaces. Large droplet particles hit the char bed and the walls of the furnace without being dried. In this study, particles of black liquor sprays were imaged using a high-speed infrared camera. Measurements were done in a functional recovery boiler in a pulp mill. Objective was to find a suitable wavelength range and settings such as integration time, frame rate and averaging for the camera.

The calorimetric method has for a long time been applied for losses measurement and energy conversion efficiency determination in electrical machines. The number of temperature sensors necessary for its successful application in the field constitutes in one of the major drawbacks of the method. The present paper shows how the usage of infrared (IR) thermal imaging techniques can reduce costs and the necessary time for the calorimetric method application.

This paper presents new procedures and a wide spectrum of experimental results based on two-dimensional distributions of the dynamic features of various IR signals captured through inspection ports of several process furnaces. All analyses were made over a few seconds using the same set of 6 narrow band filters to evaluate sequences of IR thermographic images of furnace walls, tube skins, flame and combustion products . The digital (on-line) version of this paper contains samples of these videos. The final results provide samples of quantitative descriptions, which present a more complete, often new, information about the symmetry and other properties of the combustion processes This was possible due to minor modifications to the IR camera.

IR (infrared) inspection is being used to inspect oil pipelines on the North Slope of Alaska. The object of this inspection is to detect water trapped in the foam insulation around the steel pipes before it can cause corrosion that could result in a pipeline leak. This is referred to as Corrosion Under Insulation (CUI). The same method can be used to inspect insulated pipelines containing LNG (liquid natural gas), steam, heated chemicals, cryogenic fluids, etc. As long as the temperature in the pipe is substantially different (+ or -) than the ambient temperature, the IR evaluation method can work. Analysis can predict whether it will work for a specific application and operating conditions. IR can scan multiple pipes quickly and is a good qualitative screening method for detecting water trapped in insulation. Anomalies found by IR are evaluated further using RT ("C-Arm" or other RT technique) or other NDT methods. RT is a relatively slow technique compared to IR, but it is capable of detecting both water and pipe wall thinning. When the water level is high enough to reach the steel pipeline, corrosion of the pipe can occur. In this case, the corrosion is from the outside of the pipe inward. Other corrosion and erosion may take place from the inside out. Corrosion and erosion can eventually result in a hole in the pipe, which results in a leak. Thermal modeling has been performed to predict the environmental conditions under which IR testing will be successful. IR test procedures have been written and a personnel certification program has been implemented.

Three sportswear textiles are compared, one normal and two 'special' with Ag+ ions and Carbon powder added, with different colors. The emissivity of the textiles has been measured to determine if it is increased in the 'special' textiles with respect to the normal one. The test implied some non-standard procedure due to the semitransparent nature of the textiles, in comparison with the normal procedure that is commonly used on opaque surfaces. The test is also carried out by a standard emissometry technique, based on a comparative approach with reference samples having known thermal emissivity. The results are compared and discussed.

Advancements in uncooled microbolometer technology over the last several years have opened up many commercial applications which had been previously cost prohibitive. Thermal technology is no longer limited to the military and government market segments. One type of thermal sensor with low NETD which is available in the commercial market segment is the uncooled amorphous silicon (α-Si) microbolometer image sensor. Typical thermal security cameras focus on providing the best image quality by auto tonemaping (contrast enhancing) the image, which provides the best contrast depending on the temperature range of the scene. While this may provide enough information to detect objects and activities, there are further benefits of being able to estimate the actual object temperatures in a scene. This thermographic ability can provide functionality beyond typical security cameras by being able to monitor processes. Example applications of thermography^[2] with thermal camera include: monitoring electrical circuits, industrial machinery, building thermal leaks, oil/gas pipelines, power substations, etc...^[3][5] This paper discusses the methodology of estimating object temperatures by characterizing/calibrating different components inside a thermal camera utilizing an uncooled amorphous silicon microbolometer image sensor. Plots of system performance across camera operating temperatures will be shown.

Natural gas and electric utility companies, public utility commissions, consumer advocacy groups, city governments, state governments and the federal government United States continue to turn a blind eye towards utility energy theft of service which we conservatively estimate is in excess of $10 billion a year. Why? Many in the United States have exhausted their unemployment benefits. The amounts for federal funding for low income heating assistance programs (LIHEAP) funds were cut by nearly 40% for 2012 to $3.02 billion. "At peak funding ($5.1 billion in 2009), the program was national in scale but still only had enough resources to support roughly 1/4 of the eligible households.ⁱ" Contributions to charities are down and the number of families below the poverty line who are unable to pay to heat their houses continues to rise. Many of the less fortunate in our society now consider theft and fraud to be an attractive option for their supply of natural gas and/or electricity. A record high mild winter in 2011-2012 coupled with 10-year low natural gas prices temporarily obscured the need for low income heating assistance programs (LIHEAPs) from the news and federal budgets, but cold winters will return. The proliferation of smart meters and automated meter infrastructures across our nation can do little to detect energy theft because the thieves can simply by-pass the meters, jumper around the meters and/or steal meters from abandoned houses and use them. Many utility systems were never set-up to stop these types of theft. Even with low-cost per identified thief method using aerial infrared thermography, utilities continue to ignore theft detection.

A common method for diagnosing heart health condition is to analyze blood flow rate and temperature behaviors after arterial occlusion. However, multiple factors besides heart condition could affect these behaviors. The objective of this research was to identify other factors that affect blood flow and thermal response after arterial occlusion, evaluate a mathematical model to determine thermal response after arterial occlusion, and develop an experimental model for thermal response after arterial occlusion. Twenty-eight experiments were conducted with 14 subjects to determine blood and thermal responses by using plethysmography and infrared imaging after applying arterial occlusion. Possible factors affecting blood flow and thermal responses that were investigated were: Initial finger temperature, blood pressure, body temperature, gender, and age. After determining the correlation coefficient among the mentioned factors and blood flow and thermal responses after occlusion, it was determined that only initial finger temperature and blood pressure show a strong effect. A mathematical model accounting only for the convective thermal effects, but not thermal conduction effects, was developed and tested, but was found to be insufficiently accurate in describing the thermal response by means of blood flow parameters for all of the subjects tested (error>90%). A linear regression model was then developed to relate blood flow to thermal response using two thirds of the experimental data, and was tested using one third of the data. The linear regression model was found to predict thermal response by means of blood flow response with an error rate of less than 50%.

The objective of this study was to investigate the efficacy of melding three emerging technologies: Pharmacogenomics, Modified Military Digital Infrared and Halo to establish their capability in diagnosing ultra-small breast cancers as well as other cancers. Mammography, ultrasound and MRI technologies have been available for over forty years, however, there is still no uniform utilization by women, costs continue to escalate and problems persist like high false positive rates for MRI and high false negative rates for mammography. Of the first 500 IR patients, 499 were female and 1 male. Of 550 OncoVue patients, 129 opted to undergo IR. A total of 19 were lost to follow-up. Patients who were negative on IR: 419/500 (84%). Of these, 63/419 went to biopsy because of findings of other diagnostic modalities. Of these 61/63 with negative IR had a negative biopsy. Of two missed, one was the fault of the investigator but was included. In this series 2/500 were false negative (0.4%). The sensitivity was 96% and the specificity was 79%. In total, 46 cancers were identified including five outside the breast (e.g. 2 lung cancers). A total of 92 MRIs were done and in 71/92 patients IR and MRI agreed. Using these three modalities the smallest cancer found was a 4 mm invasive cancer. The study demonstrated that these diagnostic techniques can dramatically lower cost and provide results at least as good as the older paradigms. Further research and a multicenter clinical trial are necessary to shift the paradigm of breast cancer diagnosis and treatment.

Effective laser welding of biological tissues require strict temperature control over the entire process, because the allowed temperature margin is 2K around the tissue-specific coagulation temperature. The paper presents the results of the research concerning laser tissue welding, using continuous wave laser diode, including the description of a test stand and conducted experiments. The influence of energetic and time parameters of a laser beam on the observed thermal effects is discussed and the application of fast thermal camera for the monitoring of tissue welding process is presented.

In this paper the problem of human ear detection in the thermal infrared (IR) spectrum is studied in order to illustrate the advantages and limitations of the most important steps of ear-based biometrics that can operate in day and night time environments. The main contributions of this work are two-fold: First, a dual-band database is assembled that consists of visible and thermal profile face images. The thermal data was collected using a high definition middle-wave infrared (3-5 microns) camera that is capable of acquiring thermal imprints of human skin. Second, a fully automated, thermal imaging based ear detection method is developed for real-time segmentation of human ears in either day or night time environments. The proposed method is based on Haar features forming a cascaded AdaBoost classifier (our modified version of the original Viola-Jones approach¹ that was designed to be applied mainly in visible band images). The main advantage of the proposed method, applied on our profile face image data set collected in the thermal-band, is that it is designed to reduce the learning time required by the original Viola-Jones method from several weeks to several hours. Unlike other approaches reported in the literature, which have been tested but not designed to operate in the thermal band, our method yields a high detection accuracy that reaches ~ 91.5%. Further analysis on our data set yielded that: (a) photometric normalization techniques do not directly improve ear detection performance. However, when using a certain photometric normalization technique (CLAHE) on falsely detected images, the detection rate improved by ~ 4%; (b) the high detection accuracy of our method did not degrade when we lowered down the original spatial resolution of thermal ear images. For example, even after using one third of the original spatial resolution (i.e. ~ 20% of the original computational time) of the thermal profile face images, the high ear detection accuracy of our method remained unaffected. This resulted also in speeding up the detection time of an ear image from 265 to 17 milliseconds per image. To the best of our knowledge this is the first time that the problem of human ear detection in the thermal band is being investigated in the open literature.

Monitoring development of chicken embryos allows determination of when an egg is not developing and when eggs are close to hatching for more efficient production. Research has been conducted on the effects of temperature fluctuations and light exposure on embryo development; similarities between chicken and mammal embryos; and the use of MRI, tomography, and ultrasound to view specific areas and processes within the embryo. However, there has been little exploration of the use of infrared imaging as a non-destructive method for analyzing and predicting embryonic development. In this study, we built an automated loading system for image acquisition. Pilot experiments were conducted to determine the overall scanning time and scanning frequency. A batch of fertilized eggs was scanned each day as the embryos continued to grow. The captured images were analyzed and categorized into three stages: Stage 1 (days 1 to 7), Stage 2 (days 8 to 14), and Stage 3 (days 15 to 21). The temperature data abstracted from the captured images were divided into two groups. Group 1, consisting of two-thirds of the data, was used to construct a model. Group 2, consisting of one-third of the data, was used to evaluate the predictive accuracy of the model. A three-layer artificial neural network model was developed to predict embryo development stage given a temperature profile. Results suggest that the neural network model is sufficient to predict embryo development stage with good accuracy of 75%. Accuracy can likely be improved if more data sets for each development stage are available.

Remote temperature sensing and thermal imaging can be invaluable tools for process control and optimization. Their utilization is limited within the metal processing industries, however, as bright metal surfaces are highly reflective, with low emissivity that can vary critically with oxide thickness and alloy composition. Any infrared temperature measurement is vulnerable to background reflection and limited to the uncertainty in the emissivity. An enclosure or cavity made of any material offers an approximation to blackbody radiation, as both emitted and reflected radiation are collected within the cavity, and background radiation is excluded by the geometry. By exploiting natural cavities formed during processing, emissivity-independent measurements can be made. This paper presents thermal imaging data from an aluminum rolling application. Data was gathered using Land's FTI-E imaging system. Based on an uncooled amorphous silicon array, the system provides measurement in the range 200°C to 600°C to an accuracy of ±1°C. The 320 x 240 pixels each have field of view 570:1, providing a total viewing angle of 32° by 24°. Data was processed by Land's LIPS ASPS software, which features a patented algorithm for identifying the area of true temperature measurement within the cavity. The software automatically locates the wedge as the strip is coiled, and tracks its position as the coil increases in size. Successive profile graphs are collated to form a '2D map' of the whole strip. The results demonstrate that accurate, emissivity-independent temperature measurements can be obtained from the wedge-shaped cavity formed where the sheet aluminum joins the roll.

Uncooled micro-bolometer of 17 μm pitch has been successfully applied to the micro-scale thermal analysis with a newly designed optics, the emissivity corrected procedure, and the quasi-acceleration of time frame method. The spatial resolution of 11 μm in a good balance of MTF and N.A. has been achieved for the optics of VOx FPA. It enables to visualize the exothermic latent heat of freezing biological cells at a minus temperature. The emissivity corrected microscale thermal imaging using a real time direct impose-signal system is presented both with VOx and InSb FPA.

Our group has developed a Planck physics-based model for the input/output behavior of near infrared (NIR) hyperspectral cameras. During the validation of the model, experiments conducted using an NIR hyperspectral camera have shown that, when thermal radiation is used as the camera input and no illumination is present, the output offset happens to be thermally dependent, yet independent of the wavelengths in the NIR band. In this work, the effect of the incident temperature on the amount of output offset in NIR hyperspectral cameras has been experimentally studied and introduced in our previous model for such cameras. The experimental study has been conducted using an NIR hyperspectral camera in the range of 900 to 1700 [nm] and a controlled illumination set-up, while different input temperatures have been controlled by means of black-body radiator sources. The thermal-dependent offset is modeled phenomenologically from experimental data. Initial results have shown a non-linear dependence between the offset and the temperature. This thermal-offset dependence can be used to generate new NIR hyperspectral models, new non-linear calibration procedures, and establish a basis for the study of time dependent variations of the NIR thermal-offset.

MWIR spectroscopy shows a large potential in the current IR devices market, due to its multiple applications (gas detection, chemical analysis, industrial monitoring, combustion and flame characterization, food packaging etc) and its outstanding performance (good sensitivity, NDT method, velocity of response, among others), opening this technique to very diverse fields of application, such as industrial monitoring and control, agriculture, medicine and environmental monitoring. However, even though a big interest on MWIR spectroscopy technique has been present in the last years, two major barriers have held it back from its widespread use outside the laboratory: the complexity and delicateness of some popular techniques such as Fourier-transform IR (FT-IR) spectrometers, and the lack of affordable specific key elements such a MWIR light sources and low cost (real uncooled) detectors. Recent developments in electrooptical components are helping to overcome these drawbacks. The need for simpler solutions for analytical measurements has prompted the development of better and more affordable uncooled MWIR detectors, electronics and optics. In this paper a new MWIR spectrometry device is presented. Based on linear arrays of different geometries (64, 128 and 256 elements), NIT has developed a MWIR Variable Filter Array Spectrometer (VFAS). This compact device, with no moving parts, based on a rugged and affordable detector, is suitable to be used in applications which demand high sensitivity, good spectral discrimination, reliability and compactness, and where an alternative to the traditional scanning instrument is desired. Some measurements carried out for several industries will be also presented.

Target range estimation is traditionally based on radar and active sonar systems in modern combat system. However, the performance of such active sensor devices is degraded tremendously by jamming signal from the enemy. This paper proposes a simple range estimation method between the target and the sensor. Passive IR sensors measures infrared (IR) light radiance radiating from objects in dierent wavelength and this method shows robustness against electromagnetic jamming. The measured target radiance of each wavelength at the IR sensor depends on the emissive properties of target material and is attenuated by various factors, in particular the distance between the sensor and the target and atmosphere environment. MODTRAN is a tool that models atmospheric propagation of electromagnetic radiation. Based on the result from MODTRAN and measured radiance, the target range is estimated. To statistically analyze the performance of proposed method, we use maximum likelihood estimation (MLE) and evaluate the Cramer-Rao Lower Bound (CRLB) via the probability density function of measured radiance. And we also compare CRLB and the variance of and ML estimation using Monte-Carlo.

Passive infrared gas imaging systems have been utilized in the equipment leak detection and repair in chemical manufacturers and petroleum refineries. The detection performance mainly relates to the sensitivity of infrared detector, optical depth of gas, atmospheric transmission, wind speed, and so on. Based on our knowledge, the spatial concentration distribution of continuously leaking gas plays an important part in leak detection. Several computational model of gas diffusion were proposed by researchers, such as Gaussian model, BM model, Sutton model and FEM3 model. But these models focus on calculating a large scale gas concentration distribution for a great amount of gas leaks above over 100- meter height, and not applicable to assess detection limit of a gas imaging system in short range. In this paper, a wind tunnel experiment is designed. Under different leaking rate and wind speed, concentration in different spatial positions is measured by portable gas detectors. Through analyzing the experimental data, the two parameters σ_y(x) and σ_z (x) that determine the plume dispersion in Gaussian model are adjusted to produce the best curve fit to the gas concentration data. Then a concentration distribution model for small mount gas leakage in short range is established. Various gases, ethylene and methane are used to testify this model.

As to visualize the leaking gas cloud which is not visible to the naked eyes, three categories of techniques have emerged, Backscatter Absorption Gas Imaging, Passive Thermal Imaging, and Imaging Spectrometer. Among these systems, Signal to Noise Ratio (SNR) is generally used to deduce gas leakage detection limit and leads to several performance evaluation parameters, such as Noise-Equivalent Spectral Radiance and Noise-Equivalent Concentration-Path Length. However, in most cases, measuring the SNR accurately is not accessible and usually needs auxiliary instruments. Therefore, we focus on researching a gas leakage detection model according to the general parameter of a thermal imager, Noise Equivalent Temperature Difference (NETD). Firstly, the Gas Equivalent Blackbody Temperature Difference (GEBTD) is obtained by calculating the attenuated radiation of the On-plume path and that of the Off-plume path respectively. A simplified form of GEBTD was derived by our previous paper, assuming that the work range was short and the affection of atmospheric transmission was omitted. But in this paper, more factors are considered to establish a more realistic and accurate detectivity model. The radiation of the gas cloud and the attenuation of the atmosphere are taken into account as well as the size of the leakage spot which inevitably affects the concentration path length. Secondly, the NETD and the GEBTD are compared to determine the detection capability. At last, an experiment is designed to verify the accuracy and reliability of this model on the basis of the gas cloud concentration cone distribution model.