USING NEURAL NETWORK AND PARTIAL LEAST SQUARE REGRESSION TECHNIQUES IN OBTAINING MEASUREMENTS OF ONE OR MORE POLYMER PROPERTIES WITH AN ON-LINE NMR SYSTEM

摘要

An on-line nuclear magnetic resonance (NMR) system, and related methods, are useful for predicting one or more properties of interest of a polymer. In one embodiment, a neural network is used to develop a model which correlates process variables in addition to manipulated NMR output to predict a polymer property of interest. In another embodiment, a partial least square regression technique is used to develop a model of enhanced accuracy. Either the neural network technique or the partial least square regression technique may be used in conjunction with a described multi-model or best-model-selection scheme according to the invention. The polymer can be a plastic such as polyethylene, polypropylene, or polystyrene, or a rubber such as ethylene propylene rubber.