Improving Process Monitoring Data for Nuclear Fuel Reprocessing Plants Using State Estimation and Pattern Recognition

摘要

This report presents the results of a study of the technical feasibility of using statistical methods for improving process monitoring data in a nuclear fuel reprocessing plant. The data are improved in two senses. First, instrument obser¬vations contaminated by normally present instrument noise and process uncertainties are improved in accuracy. Secondly, the instrument observations are searched for errors that represent some abnormal instrument or system operation.