This PDF file contains the front matter associated with SPIE Proceedings Volume 9105, including the Title Page, Copyright information, Table of Contents, Invited Panel Discussion, and Conference Committee listing.

Both mid-wave and long-wave IR cameras are used to measure various temperature profiles in thermoplastic parts as they are printed. Two significantly different 3D-printers are used in this study. The first is a small scale commercially available Solidoodle 3 printer, which prints parts with layer thicknesses on the order of 125μm. The second printer used is a “Big Area Additive Manufacturing” (BAAM) 3D-printer developed at Oak Ridge National Laboratory. The BAAM prints parts with a layer thicknesses of 4.06 mm. Of particular interest is the temperature of the previously deposited layer as the new hot layer is about to be extruded onto it. The two layers are expected have a stronger bond if the temperature of the substrate layer is above the glass transition temperature. This paper describes the measurement technique and results for a study of temperature decay and substrate layer temperature for ABS thermoplastic with and without the addition of chopped carbon fibers.

Thermography has an extremely important difference from the other visual image converting electronic systems, like XRays or ultrasound: the infrared camera operator usually spend hour after hour with his/her eyes looking only at infrared images, sometimes several intermittent hours a day if not six or more continuous hours. This operational characteristic has a very important impact on yield, precision, errors and misinterpretation of the infrared images contents. Despite a great hardware development over the last fifty years, quality infrared thermography still lacks for a solution for these problems. The human eye physiology has not evolved to see infrared radiation neither the mind-brain has the capability to understand and decode infrared information. Chemical processes inside the human eye and functional cells distributions as well as cognitive-perceptual impact of images plays a crucial role in the perception, detection, and other steps of dealing with infrared images. The system presented here, called ThermoScala and patented in USA solves this problem using a coding process applicable to an original infrared image, generated from any value matrix, from any kind of infrared camera to make it much more suitable for human usage, causing a substantial difference in the way the retina and the brain processes the resultant images. The result obtained is a much less exhaustive way to see, identify and interpret infrared images generated by any infrared camera that uses this conversion process.

The paper is focused on the application of uncooled MWIR imaging sensors for the monitoring of industrial welding processes: resistance spot welding, resistance seam welding and laser welding. During the last 40 years, there has been little advancement in sensor systems for inline quality control monitoring of the welding process. Most of the existing systems are oriented for current, voltage and welding force monitoring. However, the temperatures reached during the majority of the welding processes lead to infrared sensing as a powerful tool, and to the MWIR band in particular as the most useful spectral band for monitoring this type of industrial processes. Infrared image information is a powerful tool to study the energy distribution in the HAZ (Heat Affected Zone). The work presents some experimental results obtained with uncooled MWIR imaging sensors, by monitoring several welding processes. These results may be applied for real-time quality assurance of the process leading to better throughputs in industrial manufacturing. The high-speed capability of the sensors used helped also to characterize the dynamics of the welding process.

Motivation to undertake research on brain surface temperature in clinical practice is based on a strong conviction that the enormous progress in thermal imaging techniques and camera design has a great application potential. Intraoperative imaging of pathological changes and functionally important areas of the brain is not yet fully resolved in neurosurgery and remains a challenge. Extensive knowledge of the complex mechanisms controlling homeostasis (thermodynamic status of an organism being a part of it ) and laws of physics (which are the foundations of thermography), make this method very good and a simple imaging tool in comparison with other modern techniques, such as computed tomography, magnetic resonance imaging and angiography. Measurements of temperature distribution across the brain surface were performed on four rats (Wistar strain) weighing approximately 300 g each. Animals have remained under general anesthesia typically conducted using isoflurane. The brain was unveiled (the dura mater remained untouched) through the skin incision and removal of the bone cranial vault. Cerebrocortical microflow was measured using laser-Doppler flow meter. Arterial blood pressure was also measured in rat femoral artery. From the above data the cerebrovascular resistance index was calculated. Cerebral flow was modified by increasing the CO2 concentration in the inspired air to 5% for the duration of 6 minutes. Another change in cerebral flow was induced by periodic closing of right middle cerebral artery. Artery occlusion was performed by introducing a filament for a period of 15 minutes, then an artery was opened again. Measurements were carried out before, during and after the artery occlusion. Paper presents results and methodology of measurements.

Motivation to undertake research on brain surface temperature in clinical practice is based on a strong conviction that the enormous progress in thermal imaging techniques and camera design has a great application potential. Intraoperative imaging of pathological changes and functionally important areas of the brain is not yet fully resolved in neurosurgery and remains a challenge. A study of temperature changes across cerebral cortex was performed for five patients with brain tumors (previously diagnosed using magnetic resonance or computed tomography) during surgical resection or biopsy of tumors. Taking into account their origin and histology the tumors can be divided into the following types: gliomas, with different degrees of malignancy (G2 to G4), with different metabolic activity and various temperatures depending on the malignancy level (3 patients), hypervascular tumor associated with meninges (meningioma), metastatic tumor - lung cancer with a large cyst and noticeable edema. In the case of metastatic tumor with large edema and a liquid-filled space different temperature of a cerebral cortex were recorded depending on metabolic activity. Measurements have shown that the temperature on the surface of the cyst was on average 2.6 K below the temperature of surrounding areas. It has been also observed that during devascularization of a tumor, i.e. cutting off its blood vessels, the tumor temperature lowers significantly in spite of using bipolar coagulation, which causes additional heat emission in the tissue. The results of the measurements taken intra-operatively confirm the capability of a thermal camera to perform noninvasive temperature monitoring of a cerebral cortex. As expected surface temperature of tumors is different from surface temperature of tissues free from pathological changes. The magnitude of this difference depends on histology and the origin of the tumor. These conclusions lead to taking on further experimental research, implementation and further verification of the thermal imaging method and its usefulness in clinical practice. In particular the research will be undertaken on intraoperative temperature changes of active cerebral cortex areas in post-anesthetic recovery.

This paper presents work done to develop an early diagnosis and monitoring method-encompassing thermography for the detection of Diabetes Mellitus. The early detection method involves fusion of images from infrared cameras, ultrasound devices, a 3D camera and a dermatascope. The project is to develop a novel system that could be easily used by physicians to allow for early intervention, and the paper highlights the approach taken by the Skindetector project.

Crack detection during continuous direct chill casting of aluminum is a matter of economics. Determining cracks during production process saves money, energy and raw material. Of course, a non-destructive method is required for this evaluation. Because of temperature concerns conventional ultrasound is not applicable. One non-contact alternative is laser ultrasonics. In laser ultrasonics short laser pulses illuminate the sample. The electromagnetic energy gets absorbed at the surface of the sample and results in local heating followed by expansion. Thereby broadband ultrasonic waves are launched which propagate through the sample and get back reflected or scattered at interfaces (cracks, blowholes,…) like conventional ultrasonic waves. Therefore laser ultrasonics is an alternative thermal infrared technology. By using an interferometer also the detection of the ultrasonic waves at the sample surface is done in a remote manner. During preliminary examinations in the lab by scanning different aluminum studs it was able to distinguish between studs with and without cracks. The prediction of the dimension of the crack by evaluation of the damping of the broadband ultrasonic waves was possible. With simple image reconstruction methods one can localize the crack and give an estimation of its extent and even its shape. Subsequent first measurements using this laser ultrasonic setup during the continuous casting of aluminum were carried out and showed the proof of principle in an industrial environment with elevated temperatures, dust, cooling water and vibrations.

The impact of a ballistic projectile on fiber-reinforced composite panel results in a sequence of events which damage the panel, almost all of which result in the generation of heat. We use infrared cameras to spatially and temporally resolve the heat generated during impact and penetration of composite panels of ultra-high molecular weight polyethylene using several ballistic threats. We find that infrared thermography is able to identify more than half of the kinetic energy lost by the projectile during complete or partial penetration.

Composite honeycomb structures continue to be widely used in aerospace applications due to their low weight and high strength advantages. Developing nondestructive evaluation (NDE) inspection methods are essential for their safe performance. Pulsed thermography is a commonly used technique for composite honeycomb structure inspections due to its large area and rapid inspection capability. Pulsed thermography is shown to be sensitive for detection of face sheet impact damage and face sheet to core disbond. Data processing techniques, using principal component analysis to improve the defect contrast, are presented. In addition, limitations to the thermal detection of the core are investigated. Other NDE techniques, such as computed tomography X-ray and ultrasound, are used for comparison to the thermography results.

Fiber orientation in composite materials is an important feature since the material’s strength and stiffness are related to the fiber orientation. In this paper, non-destructive infrared thermography is used to assess fiber orientation of carbon/PEEK (Polyether ether ketone) laminates on the surface and subsurface of the material. Specifically, a noncontact laser lock-in thermography (LLT) technique is used for fiber orientation measurement in composite materials. LLT utilizes a modulated continuous wave (CW) laser as a heat source for lock-in thermography instead of commonly used flash and halogen lamps. Experimental results show that fiber orientation on the first (surface) and second layers of the laminate can be successfully measured using this technique.

Infrared thermography is a valuable tool for non-destructive evaluation of antique artworks. Active thermographic techniques can be applied on-site thanks to their contactless and non-invasive nature. On-site monitoring is a challenging task. The observed objects are often hard to reach and of unknown thermal and physical properties. Moreover there are usually hard constraints on the availability of the site, in terms of space and time. For these reasons the acquired data are typically inhomogeneous and need to be reorganized and post-processed, with dedicated algorithms, to enhance the analysis. The frescoes of the San Gottardo Church, located in Asolo, in the North-East of Italy, are showing multiple detachments due to the ageing process. More than 60 frescoed surfaces have been selected for evaluation via an active thermography procedure. Each area has been heated with handheld air heaters and a sequence of infrared images of the cooling process has been recorded. Several techniques are available for the post-processing of thermographic sequences. In this work standard algorithms, such as correlated contrast and principal component thermography, are compared with new ones. We propose two new algorithms, the first is based on sum and filtering, the second is an adaptation of the partial least squares method to thermography. The obtained results allow to identify and locate the most important detachments on the surfaces.

Energy sustainability is a major challenge of the 21^st century. To reduce environmental impact, changes are required not only on the supply side of the energy chain by introducing renewable energy sources, but also on the demand side by reducing energy usage and improving energy efficiency. Currently, 2D thermal imaging is used for energy auditing, which measures the thermal radiation from the surfaces of objects and represents it as a set of color-mapped images that can be analysed for the purpose of energy efficiency monitoring. A limitation of such a method for energy auditing is that it lacks information on the geometry and location of objects with reference to each other, particularly across separate images. Such a limitation prevents any quantitative analysis to be done, for example, detecting any energy performance changes before and after retrofitting. To address these limitations, we have developed a next generation thermography device called Heat Wave. Heat Wave is a hand-held 3D thermography device that consists of a thermal camera, a range sensor and color camera, and can be used to generate precise 3D model of objects with augmented temperature and visible information. As an operator holding the device smoothly waves it around the objects of interest, Heat Wave can continuously track its own pose in space and integrate new information from the range and thermal and color cameras into a single, and precise 3D multi-modal model. Information from multiple viewpoints can be incorporated together to improve the accuracy, reliability and robustness of the global model. The approach also makes it possible to reduce any systematic errors associated with the estimation of surface temperature from the thermal images.

This study is intended to establish quantitative relationships between impact damage energy and some thermal NDT parameters in application to carbon/carbon composites. When applying uniform optical stimulation, the used approach involves the synthesis of effusivity/diffusivity images respectively in one- and two-sided test procedures. Ultrasonic stimulation of composites has also proven to be attractive due to its special applicability to detect micro-cracks. However, quantitative relationships between temperature signals and impact energy are still to be studied.

Current studies suggest that thermography-based measurements may provide a feasible solution for measuring the thickness of non-metallic coatings. The focus of this research was to build an artificial neural network model to predict coating thickness using active thermography and thickness samples that have not previously been seen by the model. Best results (7.5% error) were achieved when using an ANN model with the derivative of a temperature increment’s real part Laplace transform over the real axis as the input, the gradient descent with momentum back-propagation training algorithm, and 20 hidden nodes.

Traditional homomorphic enhancement method is only attributed to the frequency domain processing, which could not enhance the image outline effectively. A better homomorphic algorithm could consider the dynamic range of image to compress and expand gray levels of the target and thus enhance image details. After the frequency domain enhancement, the deployment of mathematical morphology could smooth the outline of the image in spatial domain. This paper develops an effectively comprehensive approach to optimize the contrast of infrared image, utilizing non-linear filtering in frequency domain and top-hat and bottom-hat transforms in spatial domain. Besides, a fuzzy entropy scheme is defined to verify the improved infrared image enhancement effects. Experimental results indicate that, through the proposed method, the image details and contours can be better enhanced comparing with other methods.

InfraRed Thermal Wave Imaging (IRTWI) is one of the promising non-contact and full field inspection technique for non-destructive characterization. This technique relies on the mapping of surface temperature distribution to visualize the presence of surface and subsurface anomalies in the test material. Due to its fast and quantitative evaluation capabilities, IRTWI has gained significant importance in the characterization of Carbon Fiber Reinforced Polymers (CFRP). A CFRP specimen having flat bottom holes is considered for inspection using non-stationary Digitized Frequency Modulated Thermal Wave Imaging (DFMTWI) technique. Further depth scanning performance by using frequency domain based phase approach has been compared with recently proposed time domain phase approach.

Flaw detection and characterization with thermographic techniques in graphite polymer composites are often limited by localized variations in the thermographic response. Variations in properties such as acceptable porosity, fiber volume content and surface polymer thickness result in variations in the thermal response that in general cause significant variations in the initial thermal response. These result in a “noise” floor that increases the difficulty of detecting and characterizing deeper flaws. A method is presented for computationally removing a significant amount of the “noise” from near surface porosity by diffusing the early time response, then subtracting it from subsequent responses. Simulations of the thermal response of a composite are utilized in defining the limitations of the technique. This method for reducing the data is shown to give considerable improvement characterizing both the size and depth of damage. Examples are shown for data acquired on specimens with fabricated delaminations and impact damage.

This paper reviews applications of infrared thermal signature techniques to detection of faults and defects on electronics boards. Issues essential to the successful application of infrared techniques to electronics manufacturing and circuit card maintenance are investigated. These issues include basic know-how such as scanning time interval and screening variables; a description of the types of defects and faults these methods have been used to detect; and a comparison of infrared thermal imaging and other detection means such as X-ray and functional testers. The paper concludes with a summary of potential problems and remedies. Future directions include design for infrared diagnosis and development of integrated testing techniques for detection and root-cause analysis.

A methodology based on active infrared thermography to study and characterize hidden solder joint shapes on a multi cover PCB assembly was investigated. A numerical model was developed to simulate the active thermography methodology and was proven to determine the grand average cooling rates with maximum errors of 8.85% (one cover) and 13.36% (two covers). A parametric analysis was performed by varying the number of covers, heat flux provided, and the amount of heating time. Grand average cooling rate distances among contiguous solder joint shapes, as well as solder joints discriminability, were determined to be directly proportional to heat flux, and inversely proportional to the number of covers and heating time. Finally, a mathematical model was developed to determine the appropriate total amount of energy needed to discriminate among hidden solder joints with a “good” discriminability for one and two covers, and a “regular” discriminability for up to five covers. The mathematical model was proven to predict the total amount of energy to achieve a “good” discriminability for one cover within a 10% of error with respect to the experimental active thermography model.

Among various widely used Infrared Thermal Non-destructive Testing (IRTNDT) modalities, non-stationary thermal wave imaging (NSTWI) methods have proved to be an indispensable approach for the inspection and evaluation of various materials. Growing concerns of surface and subsurface defect detection capabilities with moderate peak power heat sources than the widely used conventional pulse based thermographic methods and in a reasonably less testing time compared to sinusoidal modulated lock-in thermography, make these NSTWI techniques invaluable for this field. The present work highlights a comparative study on various NSTWI techniques, further experimental results are presented to find their defect detection capabilities by taking signal to noise ratio (SNR) into consideration.

In recent years, fatigue crack propagations in aged steel bridge which may lead to catastrophic structural failures have become a serious problem. For large-scale steel structures such as orthotropic steel decks in highway bridges, nondestructive inspection of deteriorations and fatigue damages are indispensable for securing their safety and for estimating their remaining strength. As conventional NDT techniques for steel bridges, visual testing, magnetic particle testing and ultrasonic testing have been commonly employed. However, these techniques are time- and labor- consuming techniques, because special equipment is required for inspection, such as scaffolding or a truck mount aerial work platform. In this paper, a new thermography NDT technique, which is based on temperature gap appeared on the surface of structural members due to thermal insulation effect of the crack, is developed for detection of fatigue cracks. The practicability of the developed technique is demonstrated by the field experiments for highway steel bridges in service. Detectable crack size and factors such as measurement time, season or spatial resolution which influence crack detectability are investigated.

A novel binary complementary (Golay) coded infrared thermal non destructive testing and evaluation approach is introduced for characterization of mild steel sample having flat bottom holes as defects. The resultant correlation results of these individual Golay complementary codes used to reconstruct a short duration high peak power compressed pulse to extract the subsurface features hidden inside the test sample. In this paper, a finite element method has been used to model a low carbon steel sample containing flat bottom holes as sub-surface defects located at different depths. Results show the depth scanning capabilities of the proposed Golay complementary coded excitation scheme as a promising testing and evaluation method to detect the subsurface defects with improved resolution and sensitivity.