Abstract

Due to their capability to evaluate the microscopic mobility of polymers, dielectric sensors are increasingly used for in-situ cure monitoring of thermoset composites. More than a dozen cure correlation methods have been proposed in literature to date, each of which focuses on a specific dielectric parameter. However, the wide variety of techniques have not been compared nor robustly evaluated for accuracy and repeatability. This study collects dielectric signal data (dissipation factor, impedance, ionic conductivity/viscosity, loss factor, and permittivity) during cure of an out-of-autoclave thermoset prepreg and conducts a systematic evaluation of the five dielectric parameters to prove that the parameters can be used interchangeably and, in some cases, can deliver complementary information. By correlating features of dielectric graphs to both experimentally measured and numerically simulated cure state events, a master list of correlation techniques is presented. The proposed techniques have improved accuracy and repeatability in comparison to the existing analysis techniques.

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