Technological advances have been observed due to continuing discoveries and applications of materials exhibiting novel or enhanced properties, which offer superior performance to conventional products and processes. When these materials and parts are used in some critical applications and directly impact the safety and success of a project, it is crucial to ensure their quality and reliability. NDE technologies have rapidly evolved over the past years. The application of these technologies has improved the quality and the reliability of components that are being used in various fields. This work aims to develop a reliable NDE framework that can characterize the materials with complex shapes and/or properties. The studies will mainly focus on the electromagnetic methods, design/optimize the sensing system, and processing of the data to utilize information from multi-frequency and multi-parameter testing. Strain distribution is an essential indicator of stress concentration, damage initiation, and evolution. Many dielectric materials sustain considerable strain before failure. The first part of the research deals with designing a near-field microwave high-resolution imaging (NMHI) system that is able to estimate very large deformation for dielectric materials. The main contributions of this part of the research are the following: a) designing a rapid imaging system that is able to provide high-resolution information of the OUT. b) a multimodality data fusion technique is applied to evaluate the strain of Polyamide 11 (PA-11) through simulations and experiments. c) the relationship between near-field microwave signal measured from the sample and the sample's mechanical properties has been studied. The second part of the research focuses on the design of a root phenotyping system. The opaque surrounding environment of the roots and the complicated growth process make the in-situ and non-destructive root phenotyping faces significant challenges, which also raises tremendous research interest. Existing methods for root phenotyping are either unable to provide high-precision and high accuracy in-situ detection or change the surrounding root environment and are destructive to root growth and health. The contributions of this part of the research are the following: An ultra-wideband microwave imaging system is designed and optimized for non-destructive root phenotyping with the potential of in-situ monitoring. The system has been developed to estimate the location and shape of the root with the soil's background noise. The capability to provide the size and localization information of single and multiple roots demonstrates the simulation framework's robustness. Precise results and high imaging quality of the reconstruction achieved from the experiment studies validate the proposed microwave imaging method's accuracy. The non-iterative TR algorithm proposed for signal processing is computationally efficient, enabling rapid roots localization. This work also shows its ability to real-time monitor the root system in a natural soil environment. The advantage of its fast scanning ability and robustness enables the microwave imaging technique to be deployed in fields for scanning a large volume of soil and accessing the state of roots in a real-time manner. The third part of the research deals with designing portable NDE sensors to meet different scanning requirements. Many constraints need to be considered when designing the NDE sensing system for the robot. The sensor's footprint is limited by the design of the robotic system as well as the complexity of testing structures. The allowable maximum power consumption of the entire system is constrained by the available power supply unit on the robot. Many environmental conditions could affect the NDE results obtained from the robotic actuating and sensing. Such would add inevitable uncertainties to the acquired data or restrict actuation access, lowering the fidelity and resolution of NDE data used for further damage assessment and analysis. To overcome these aforementioned challenges and obtain optimized sensing outcomes, the proposed NDE sensors were customized to fit in the robotic system and workspace environment for power plant boiler inspection. These optimizations lead to a low-cost, lightweight, non-contact, and simplified NDE setup.
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