System and method for recognizing and compensating for invalid regression model applied to abnormal situation prevention

摘要

A system for preventing abnormal situations in process plants is provided. A polynomial regression model is employed to predict values of a monitored variable based on measured samples of a load variable. An abnormal situation is detected when a predicted value of the monitored variable differs from a measured value of the monitored variable by more than a predetermined. The system recognizes when a data model is invalid and takes steps to compensate for the invalid model.