D. Srinivasagupta ([email protected]) and B. Joseph ([email protected]) are now with

This article examines the operational characteristics of the injected pultrusion (IP) process using a bench-scale unit. The distributed, nonlinear nature of the process makes routine process operations and quality control difficult. In our prior work [1], a 3-dimensional dynamic model based on mass, momentum and energy transport was developed. This processing model is validated using experimental data from the bench scale unit. Experiments were designed to verify the steady state and dynamics of the process model. The model predictions were validated with the primary measurements of temperature and pressure profiles, and cure, as well as secondary measurements of pull force and part exit temperature. While there was good agreement with the observed data, the experimental results indicate the need for better pull-force models and improved measurement and feedback stabilization techniques

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Measurement error due to sensor degradation (fouling, mis-calibration etc.) is more difficult to identify compared to catastrophic sensor failure. Passive methods previously proposed for sensor-level monitoring are based on power spectrum or multi-scale analysis of sensor data. These methods have limitations caused by not accounting for various noise sources, and assumptions about sensor noise characteristics; thus resulting in false and missed alarms. In this paper, an on-line sensor fault detection scheme based on identification of sensor response characteristics is proposed and evaluated. We develop both robust passive and active in-situ techniques to identify sensor response characteristics that relate directly to its health. Using the identified sensor model, various kinds of sensor faults are quantified and mapped into the model parameters. A dynamic model-based estimator is proposed for data reconciliation. These ideas were experimentally validated using thermocouples, flow-meters, and resistance thermometric devices (RTD) on laboratory scale processes. The proposed approach was seen to accurately quantify the sensor model parameters and aid in measurement reconstruction. Keywords: Sensor Fault Detection, Measurement Validation, In-situ Sensor Modeling

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Injected pultrusion (IP) is a continuous process for manufacture of fiber-reinforced polymer composites. Measurement of the pull-force encountered in the pulling of the fibers through the injected pultrusion die is a commonly used indicator of the process health. A review of pull-force modeling reveals drawbacks in the current model recently developed for the IP process. A qualitative analysis of the scaling factors involved in the IP process suggests that dies of smaller cross-section are more prone to operational problems such as die seizure and runaway conditions on the pull-force. Our recent experimental studies on a bench-scale IP process as well as existing literature support these conclusions. These experimental insights are used to suggest improvements in the pull-force model, by incorporating variations due to fiber loading, shrinkage, and contact friction. The improved pull-force model gives better qualitative agreement with experimental observations