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 application of piezoelectric sensors such as the ultrasonic transducer has significantly enhanced the fields of nondestructive evaluation (NDE). Their application of piezoelectric materials allows for the sensing of low energy, high frequency acoustic emission (AE) events such as fatigue cracking in metals and delamination in composites. Utilizing the physical characteristics of these AE waves, the location of these structural defects can then be source located by means of time-of-flight trilateration. The real time sensing of such events has led to the field of structural health monitoring (SHM) and has revolutionized NDE. Furthermore, with the application of modern micro-electromechanical system-based (MEMS) technology, the fields of NDE and SHM can be improved greatly, and sensing instrumentation simplified. A novel piezoresistive-based MEMS strain sensor is presented as this improvement to NDE and SHM. The ultrathin silicon membrane-based (USM) strain sensor's ability to capture an AE signal is demonstrated by a Hsu-Nielsen source and shows comparable frequency content to a commercial piezoceramic ultrasonic transducer. To the knowledge of the authors, this makes the USM strain sensor the first known piezoresistive strain sensor capable of recording low energy AE. The novel improvements to NDE and SHM arise from the sensor's low minimum detectable strain and wide frequency bandwidth, enabling a dual-use application of both AE and static strain sensing. The USM sensor's ability to document quasi-static bending is demonstrated and once again compared with an ultrasonic transducer, which provides no significant response. This dual-use application is proposed to effectively combine the uses of both strain and ultrasonic transducer sensor types within one sensor, lending itself novel and useful to NDE and SHM. The potential benefits include enhanced sensitivity, reduced sensor size and cost, and reduced instrumentation complexity. / Master of Science / Visual inspection for cracks and defects has long been staples of assessing structural health throughout human history. These surface imperfections are an obvious hindrance to structural integrity and routine observation and inspection is needed to ensure a structure's safety. With the progression of technology and the discovery of piezoelectric materials, more advanced methods have been devised to detect and source locate not only surface level but sub-surface cracking. This has been accomplished through the use of piezoelectric ultrasonic transducers to monitor the propagation of acoustic emission (AE) vibrations, which are the result of energy redistribution by events such as cracking. The remote monitoring of AE events has led to the growth of the nondestructive evaluation (NDE) field, where these cracks and defects can be located by the detection of their AE source. These transducers, however, are met with limitations in their applications. Operating off the piezoelectric effect allows for a superb response to low energy, high frequency excitation characteristic of AE, but results in no response to quasi-static strain measurements, such as that of a slowly applied bending load on a plate. In the work herein, modern micro-electromechanical system (MEMS) based technology is utilized to devise a sensor capable of both AE and static strain measurements. The dual sensing of both of these measurements can allow for the source location of cracking events along with the monitoring of structure strain, effectively combining the use of two sensors into one. This dual-application use can have a great impact on the evaluation of critical structures like bridges and aircraft and simplify and reduce costs inherent to nondestructive evaluation.

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Carbon ber composites have become popular in aerospace structures and applications due to their light weight, high strength, and high performance. Recently, scientists have begun investigating hybrid composites that include fibers and particulate fillers, since they allow for advanced tailoring of mechanical properties, such as improved fatigue life. This project investigated a hybrid carbon ber reinforced polymer (HCFRP) that includes carbon fiber and additional alumina nanoparticle fillers, which act as embedded nano stress-sensors. Utilizing the piezospectroscopic e ect, the photo-luminescent spectral signal of the embedded nanoparticles has been monitored as it changes with stress, enabling non-contact stress detection of the material. The HCRFPs stress-sensitive properties have been investigated in-situ using a laser source and a tensile mechanical testing system. Hybrid composites with varying mass contents of alumina nanoparticles have been studied in order to determine the e ect of particle content on the overall stress sensing properties of the material. Additionally, high resolution photo-luminescent maps were conducted of the surfaces of each sample in order to determine the particulate dispersion of samples with varying alumina content. The dispersion maps also served as a method of quantifying particulate sedimentation, and can aid in the improvement of the manufacturing process. The results showed that the emitted photo-luminescent spectrum can indeed be captured from the embedded alumina nanoparticles, and exhibits a systematic trend in photo-luminescent peak shift with respect to stress. The stress maps showed a linear increase in peak shift up to a certain critical stress, and matched closely with the DIC strain results. Therefore, the non-contact stress sensing results shown in this work have strong implications for the future of structural health monitoring and nondestructive evaluation (NDE) of aerospace structures.

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