Knowledge-based detection of out-of-control outputs in process control

A system is described which combines statistical process control principles and knowledge of the process dynamics to automatically detect out-of-control conditions due to certain types of deterministic disturbances in a control process. This system employs nonlinear filtering techniques to detect three features (peaks, steps and ramps) in the output signal. These features are examined to produce a set of out-of-control events. Corrective action can then be taken to bring the process back into an in-control condition.<
>