Polymer Engineering Faculty Research

Title

On-Line Crystallinity Measurement Using Laser Raman Spectrometer and Neural Network

Document Type

Article

Publication Date

Spring 4-1999

Abstract

A neural network is configured and trained to measure the polymer crytallinity in real time and non-intrusive manner. After the training, input to the neural network becomes the laser Raman spectrum at selected ferquencies and the output from the network is the current crystallinity of polymer. In order to train the neural network, a training data set is constructed where the crystallinities corresponding to a given set of Raman spectra are pre-determined by the small angle light scattering (SALS) methodology. The technique is applied to measure the crystallinity of low-density thin polyethylene (LDPE) film. A typical sampling period for the determination of the crystallinity is around 12 s. The technique is compared to the principal component analysis that uses the same input data for calibration.

Publication Title

ISA Transactions

Volume

38

Issue

2

First Page

139

Last Page

148