Conductive nanofiller-modified composites have received a lot of attention from the structural health monitoring (SHM) research community in recent years because these materials are piezoresistive (i.e. they have deformation and damage-dependent electrical conductivity) and are therefore self-sensing. To date, the vast majority of work in this area has utilized direct current (DC) interrogation to identify and/or localize damage. While this approach has been met with much success, it is also well known that nanofiller-modified composites possess frequency-dependent electrical behavior. This behavior can be roughly modeled as a parallel resistor-capacitor circuit. However, much less work has been done to explore the potential this frequency-dependent behavior for damage detection. To this end, the work herein presented covers some preliminary results which leverage high-frequency electrical interrogation for damage detection. More specifically, carbon nanofiber (CNF)/epoxy specimens are produced and connected to an external inductor in both series and parallel configurations. Because the CNF/epoxy electrically behaves like a resistor-capacitor circuit, the inclusion of an inductor enables electrical resonance to be achieved. Changes in resonant frequency are then used for rudimentary damage detection. These preliminary results indicate that the potential of SHM via the piezoresistive effect in nanofiller-modified composites can be considerably expanded by leveraging alternating current (AC) interrogation and resonant frequency principles.
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Damage Detection in Nanofiller-Modified Composites With External Circuitry via Resonant Frequency Shifts
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Tallman, TN. "Damage Detection in Nanofiller-Modified Composites With External Circuitry via Resonant Frequency Shifts." Proceedings of the ASME 2018 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 2: Mechanics and Behavior of Active Materials; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies. San Antonio, Texas, USA. September 10–12, 2018. V002T05A007. ASME. https://doi.org/10.1115/SMASIS2018-8008
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