Feed-forward adaptive control of resin transfer molding (RTM) processes is crucial for producing a high yield of usable parts for industrial applications. The enabling technique for this process is non-invasive monitoring of the fill-front position and the degree of cure of the resin as it is injected into the mold. Successful implementation of a sensing system capable of meeting these criteria will result in a high yield of composite parts that can be used for the next generation of aircraft. This article articulates the possibility of a hybrid sensing system for multiparameter monitoring during RTM processes. It addresses the fundamental engineering trade-offs between penetration depth and signal strength, discussing how to account for fringing electric field (FEF) effects present in the system. FEF effects hinder the measurement accuracy of the sensor system. This article describes how these effects are addressed using a mapping algorithm that is developed using numerical simulations of the experimental setup. The experimental setup utilizes a rectangular RTM tool and a water-glycerin mixture which simulates mechanical properties of epoxy resins, prior to cure. Modeling of the FEF effects helps to achieve high measurement accuracy of the fill front location.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.