Automated In-Process Cure Monitoring of Composite Laminates Using a Guided Wave-Based System With High-Temperature...

Traditional methods for monitoring composite cure rely on post-cure inspection or limited in-situ sensors. These approaches often miss critical transitions during processing. While prior research has shown that guided waves can detect material state changes, their application to real-time cure monitoring remains limited. The need for continuous, non-invasive monitoring during cure has motivated new methods. This gap motivated the development of a guided wave-based system. No prior work had resolved how to integrate piezoelectric transducers into cure processes. This study addresses that uncertainty. The focus is on capturing physical and state transitions in real time. The goal is to improve quality control in composite manufacturing.

The aim was to develop a system for monitoring composite cure in real time using guided waves. The specific problem is the lack of continuous feedback during critical cure stages. This work tests whether guided wave amplitude and velocity can track cure progress. The motivation comes from the need for consistent composite part quality. The researchers propose using piezoelectric transducers to excite and detect guided waves. This approach allows monitoring during the cure cycle. The study seeks to validate the feasibility of this method. The goal is to enable closed-loop control for manufacturing.

The team used high-temperature piezoelectric transducers as actuators and sensors. These devices were embedded in composite panels made from IM7/8552 prepreg. The setup allowed excitation and sensing of guided waves during oven curing. The guided wave signals were measured in terms of voltage output. The amplitude was tracked using normalized peak voltage metrics. The group velocity of waves was analyzed during state transitions. The system was validated against RAVEN software simulations. The method focused on capturing gelation and vitrification stages.

The system successfully identified key cure transitions using guided wave data. Amplitude changes were linked to viscosity and degree of cure. Group velocity shifts correlated with Tg and mechanical property changes. The normalized peak voltage metric provided consistent tracking of wave behavior. Gelation and vitrification stages were clearly detected. The data matched predictions from the RAVEN model. The results showed feasibility for in-process monitoring. This approach may enable closed-loop control for composite manufacturing.

The authors state that guided wave monitoring can track critical cure parameters. They propose that amplitude and velocity metrics are useful for in-process tracking. The system demonstrated the ability to detect gelation and vitrification. The results suggest that this method supports quality control in composites. The system aligns with semi-empirical modeling predictions. The researchers suggest that this approach may improve process consistency. The findings support the feasibility of real-time monitoring. The work represents progress toward automated composite manufacturing.