Partial least square regression techniques in obtaining measurements of one or more polymer properties with an on-line nmr system
US5675253A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Jan 16, 1996 |
| Grant date | Oct 7, 1997 |
| Priority date | — |
| Expiry date | Jan 16, 2016 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01N24/082
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.