Capacitance-Based Sensor with Layered Carbon-Fiber Reinforced Polymer and Titania-Filled Epoxy

Date
2019-07-29
Authors
Yan, Jin
Downey, Austin
Chen, An
Laflamme, Simon
Hassan, Sammy
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Abstract

Advances in intelligent infrastructure can be achieved through the use of novel materials for increased system-level efficiency and multifunctionality. Carbon Fiber-Reinforced Polymer (CFRP) has been widely used in strengthening, rehabilitating, and retrofitting of existing structures because of its speed of deployment, low maintenance requirement, and high strength-to-weight ratio. In this work, the authors propose a novel method to augment CFRP with self-sensing capabilities. The sensor consists of two CFRP layers separated by a titania-filled epoxy dielectric layer, therefore forming a parallel plate capacitor. Sensing capability can be achieved through variations in the sensor’s capacitance provoked by strain, therefore providing an additional function that could be leveraged for structural health monitoring and structural health management purposes. Comprehensive testing, including (1) sensing properties on sensors with and without titania-doped epoxy and (2) electromechanical test on tension specimens subjected to both static and dynamic loading, was conducted. The test results show that doping the titania filler within the epoxy matrix can improve the sensor’s sensitivity. The gauge factor is 0.92 under static load and decreases with the increasing frequency up to 1 Hz. Therefore, it can be concluded that CFRP can be used as a self-sensing sensor without affecting its mechanical properties.

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This is a manuscript of an article published as Yan, Jin, Austin Downey, An Chen, Simon Laflamme, and Sammy Hassan. "Capacitance-Based Sensor with Layered Carbon-Fiber Reinforced Polymer and Titania-Filled Epoxy." Composite Structures (2019): 111247. DOI: 10.1016/j.compstruct.2019.111247. Posted with permission.

Keywords
Capacitor, Multifunctional material, Strain sensing, Carbon fiber reinforced polymer, Composite, Structural health monitoring
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