This research project on the campus of Southern Illinois University Carbondale is an extension to the inquiry into the feasibility and reliability of the technology known as Digital Laser Speckle Image Correlation (DiLSIC). This is a hybrid approach of combining two existing technologies. The first being Digital Image Correlation (DIC) which is a nondestructive evaluation commonly used to find displacement, in-plane strain, as well as deformation. The second being the of laser speckle patterns. This hybrid has achieved level of resolution measured to be 3.4μ. DiLSIC increases the application ability of the DIC technique to situations that generally would not be an option to use. DiLSIC needs no artifact speckle patterns to be applied to the specimen as a preparation for nondestructive testing. In DIC testing, the surface of a specimen must artifact speckles applied to the subject surface. Often the application of artifact speckles is not desirable or possible. DiLSIC is an acceptable alternative to the previously discussed industry-wide practice. This method broadens the usage of the DIC technique to situations which previously were not possible. This technology can identify, quantify, and detect the distribution of strain and stress concentrations in composite structures. For this study, a honeycomb-backed glass fiber reinforced polymer (GFRP) panel from a Cessna aircraft exterior luggage door was obtained and a defect panel is created. The panel is constructed with one area containing a repair compliant with manufacturer standardized methods and a repair area is not compliant and consists of multiple incorrect repair steps. An area with no repair is also tested to act as a control for comparison and quantification. The results for the inspected areas showed a linear strain increase in the noncompliant repair. The data plot for the compliant repair showed a trend of following the same basic curve as the no repair area. A verification process follows the DiLSIC testing consisting of using Infrared Thermography, Air-coupled ultrasonic, and white light artifact speckle DIC. These tests show DiLSIC is a viable alternative to the testing that is available in the industry. DiLSIC can detect defect location, size, geometry and map strain to determine the difference between compliant and noncompliant repairs when compared to a base level non-repair area

Characterizing hidden solder joint shapes is essential for electronics reliability. Active thermography is a methodology to identify hidden defects inside an object by means of surface abnormal thermal response after applying a heat flux. This research focused on understanding, modeling, and predicting hidden solder joint shapes. An experimental model based on active thermography was used to understand how the solder joint shapes affect the surface thermal response (grand average cooling rate or GACR) of electronic multi cover PCB assemblies. Next, a numerical model simulated the active thermography technique, investigated technique limitations and extended technique applicability to characterize hidden solder joint shapes. Finally, a prediction model determined the optimum active thermography conditions to achieve an adequate hidden solder joint shape characterization. The experimental model determined that solder joint shape plays a higher role for visible than for hidden solder joints in the GACR; however, a MANOVA analysis proved that hidden solder joint shapes are significantly different when describe by the GACR. An artificial neural networks classifier proved that the distances between experimental solder joint shapes GACR must be larger than 0.12 to achieve 85% of accuracy classifying. The numerical model achieved minimum agreements of 95.27% and 86.64%, with the experimental temperatures and GACRs at the center of the PCB assembly top cover, respectively. The parametric analysis proved that solder joint shape discriminability is directly proportional to heat flux, but inversely proportional to covers number and heating time. In addition, the parametric analysis determined that active thermography is limited to five covers to discriminate among hidden solder joint shapes. A prediction model was developed based on the parametric numerical data to determine the appropriate amount of energy to discriminate among solder joint shapes for up to five covers. The degree of agreement between the prediction model and the experimental model was determined to be within a 90.6% for one and two covers. The prediction model is limited to only three solder joints, but these research principles can be applied to generate more realistic prediction models for large scale electronic assemblies like ball grid array assemblies having as much as 600 solder joints.

[pt] Esta tese associa duas técnicas de fronteira na área de Ensaios Não-Destrutivos magnéticos, que são a utilização do magnetômetro supercondutor SQUID como instrumento de medida e de Redes Neurais como ferramentas de análise dos sinais detectados. Medidas pioneiras com o SQUID foram realizadas em amostras de aço e de alumínio contendo defeitos diversos, e foram idealizados e implementados dois Sistemas Neurais, os quais utilizaram combinações de vários tipos de redes neurais para, a partir do campo magnético medido, obter informações a respeito da geometria dos defeitos, possibilitando assim estimar sua gravidade. / [en] This thesis combines two state-of-the-art techniques in the area if magnetic Nondestructive Evaluation, that is, the application of the superconducting magnetometer SQUID as the magnetic sensor, and the use of Neural Networks as analysis tools for the detected magnetic signals. Pioneering measurements using the SQUID have been made in steel and aluminum samples with various types of flaws, and two Neural Systems have been implemented, based on the combination of several neural networks algorithms. Such systems aim to, based on the measured magnetic field, obtain information about defect geometry, thus allowing the assessment of defect severity.

[pt] Desenvolveu-se um método para Ensaios Não-Destrutivos de placas condutoras, utilizando o dispositivo supercondutor conhecido como SQUID (Superconducting Quantum Interference Device), disponível no Laboratório de Supercondutividade Aplicada e Magnetismo do Departamento de Física da PUC- Rio. O trabalho pode ser dividido em duas áreas: método experimental para obtenção das medidas magnéticas e algoritmos de processamento de imagens para realçar estes dados. / [en] It was developed a Nondestructive Evaluation method for conducting plates, using the superconducting device known as SQUID (Superconducting Quantum Interference Device), which is available in the Laboratory of Applied superconductivity and Magnetism of the Departament of Physics of PUC-Rio. The work may be separated in two fields: experimental method for obtaining the magnetic measures and image processing algorithms used to enhance this data.

Digital Laser Speckle Image Correlation (DiLSIC) is a technique that utilizes a laser generated speckle pattern with Digital Image Correlation (DIC). This technology eliminates the need to apply an artifact speckle pattern to the surface of the material of interest, and produces a finer speckle pattern resulting in a more sensitive analysis. This investigation explores the parameters effecting laser speckle patterns for DIC and studies DiLSIC as a tool to measure surface strain and detect subsurface defects on pressure vessels. In this study a 632.8 nm 30 mW neon-helium laser generated the speckle pattern by passing through the objective end of an objective lens. All experiments took place in a lab setting on a high performance laminar flow stabilizer optical table.This investigation began with a deeper look at the camera settings that effect the effectiveness of using laser speckles with DIC. The first studies were concentrated on the aperture size (f-stop), shutter speed, and gain (ISO) of the camera. Through a series of zero-correlation studies, translation tests, and settings studies, it was discovered that, much like white light DIC, an increased gain allowed for more noise and less reliable measurements when using DiLSIC. It was shown that the aperture size and shutter speed will largely depend on the surface composition of the material, and that these factors should be investigated with each new sample of different surface finish.To determine the feasibility of using DiLSIC on pressure vessels two samples were acquired. The first was a standard ASTM filament wound composite pressure vessel (CPV) which had an upper load limit of 40 psi. The second was a plastic vessel that had internal subsurface defects added with the use of an air pencil grinder. Both vessels were put under a pressure load with the use of a modified air compressor that allowed for multiple loading cycles through the use of a pressure relief valve. The CPV was mapped out in 10-degree increments between the 90° and 180° markings that were on the pressure vessel, occurring in three areas, each one inch apart. The CPV had a pressure load applied to at 10, 20, 30,and 40 psi. DiLSIC was able to measure increasing displacement with increased loading on the surface of the CPV, however with a load limit of 40 psi no strains were detected. The plastic vessel had known subsurface defects, and these areas were the focus of the investigation. The plastic vessel was loaded with a pressure load at 5, 10, 12, 15, 17, and 20 psi. The 5 psi loaded image was used as a reference image for the correlation and decorrelation consistently occurred at 20 psi. This investigation proved that DiLSIC can detect and locate subsurface defects through strain measurement. The results were verified with traditional white light DIC, which also showed that the subsurface defects on pressure vessels were detectable. The DIC and DiLSIC results did not agree on maximum strain measurement, with the DiLSIC prediciting much larger strains than traditional DIC. This is due to the larger effect out-of-plane displacement has on DiLSIC. DiLSIC was able to detect subsurface defects on a pressure vessel. The median measured hoop strain was in agreement for DiLSIC, DIC and the predicted hoop strain for a wall thickness of 0.1 inches. However, DiLSIC also produced unreliable maximum strain measurements. This technique shows potential for future applications, but more investigations will be needed to implement it for industrial use. A full investigation into the parameters surrounding this technique, and the factors that contribute the most to added noise and unreliability should be conducted. This technology is being developed by multiple entities and shows promising results, and once further advanced could be a useful tool for rapid surface strain measurement and subsurface defect detection in nondestructive evaluation applications. Therefore, it is recommended to continue further investigations into this technology and its applications.

This research aims to investigate the application of infrared thermography (IRT) as a method of nondestructive evaluation (NDE) for the detection of defects in the rail base area. Rails have to withstand harsh conditions during their application. Therefore, defects can develop in the base area of rails due to stresses such as bending, shear, contact, and thermal stresses, fatigue, and corrosion. Such defects can cause catastrophic failures in the rails, ultimately leading to train derailments. Rail base defects due to fatigue and corrosion are difficult to detect and currently there are no reliable or practical non-destructive evaluation (NDE) methods for finding these types of defects in the revenue service. Transportation Technology Center, Inc. (TTCI) had previously conducted a research on the capability of flash IRT to detect defects in rail base area based on simulation approach. The research covered in this thesis is the continuation of the same project.In this research, three rail samples were prepared with each containing a notched-edge, side-drilled holes (SDHs), and bottom-drilled holes (BDHs). Two steel sample blocks containing BDHs and SDHs of different sizes and depths were also prepared. Preliminary IRT trials were conducted on the steel samples to obtain an optimal IRT setup configuration. The initial inspections for one of the steel samples were outsourced to Thermal Wave Imaging (TWI) where they employed Thermographic Signal Reconstruction (TSR) technique to enhance the resulting images. Additional inspections of the steel samples were performed in the Southern Illinois University-Carbondale (SIUC) facility. In case of the rail samples, the SDHs and the notched-edge reflectors could not be detected in any of the experimental trials performed in this research. In addition, two more rail samples containing BDHs were prepared to investigate the detection capabilities for three different surface conditions: painted, unpainted, and rusted. The painted surface provided a best-case scenario for inspections while the other conditions offered further insight on correlating the application to industry-like cases.A 1300 W halogen lamp was employed as the heat source for providing continuous thermal excitation for various durations. Post-processing and analysis of the resulting thermal images was performed within the acquisition software using built-in analysis tools such as temperature probes, Region of Interest (ROI) based intensity profiles, and smoothing filters. The minimum defect diameter to depth (aspect) ratio detected in preliminary trials for the steel sample blocks were 1.0 at a diameter of 4.7625 mm (0.1875 in) and 1.5 at a diameter of 3.175 mm (0.125 in). For the inspection of painted rail sample, the longest exposure times (10 sec) provided the best detection capabilities in all sets of trials. The three holes having aspect ratio greater or equal to 1.0 were indicated in the thermal response of the painted and rusted samples while only the two holes having aspect ratio greater or equal to 1.5 were indicated in the unaltered sample. Indications of reflectors were identified through qualitative graphical analysis of pixel intensity distributions obtained along a bending line profile. The results obtained from the painted sample provided a baseline for analyzing the results from the unpainted and rusted rail samples. This provided an insight on the limitations and requirements for future development. The primary takeaway is the need for an optimized heat source. Poor contrast in the resulting image for the unpainted and rusted rail samples is experienced due to both noise and lack of penetration of the heat energy. This could have been due to decreased emissivity values. Moreover, the excitation method employed in this research does not comply with current industry standards for track clearances. Therefore, exploration of alternative excitation methods is recommended.

The use of electromagnetic waves as a nondestructive evaluation technique to evaluate Portland cement concrete (PCC) structures is based on the principle that a change in the structure, composition, or properties of PCC results in a change in its dielectric properties. The coaxial transmission line is one of the few devices that can measure the dielectric properties of PCC at a frequency range of 100-1000 MHz. A coaxial transmission line developed at Virginia Tech was used to study the effect of moisture, type of aggregate, water/cement ratio, curing period, admixture type (microsilica, superplasticizer, and shrinkage admixture), and chloride content on the dielectric properties of PCC. Measurements were conducted in the time domain and converted to the frequency domain using Fast Fourier Transform. The research found that an increase in the moisture content of PCC resulted in an increase in the dielectric constant. Mixes containing limestone aggregate had a greater dielectric constant than those containing granite. The dielectric constant decreased with curing period due to the reduction in free water availability. Mixes containing higher water/cement ratios exhibited a higher dielectric constant, especially in the initial curing period. The admixtures did not significantly affect the dielectric constant after one day of curing. After 28 days of curing, however, all three admixtures had an effect on the measured dielectric constant as compared to control mixes. Chloride content had a significant effect on the loss part of the dielectric constant especially during early curing. A relationship was also established between the chloride permeability (based on conductance measurements) of PCC and its dielectric constant after 75 days of moist curing. / Master of Science

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The time reversal (TR) process manipulates a system's impulse response in order to focus a peak of acoustic energy at a specific location in space and time. This technique has been implemented in both fluid and solid media for purposes ranging from communications to source localization. This thesis will examine both the implementation and processing of TR for nondestructive evaluation in steel, specializing in nonlinear detection methods. A series of steel samples are inspected for stress corrosion cracking (SCC) using TR focusing to excite nonlinearities inherent in cracks. It is determined that SCC exists in the expected regions of the steel samples and that an induced increase in SCC corresponds to an increase in detected nonlinearity. In addition to this, a study is shown wherein TR signal processing is optimized for the detection of cracks. The TR impulse response is modified in a number of ways with the primary goal of increasing the amplitude of the TR focus. Each of these modifications is experimentally scrutinized for characteristics necessary for application to nondestructive evaluation, and ultimately one is chosen that amplifies TR focusing without increasing system nonlinearity. The optimized technique, decay compensation TR, is employed in the detection of SCC and is found to be as or perhaps even more successful than typical TR nondestructive evaluation methods.