| Popis: |
Oscillations in process plants degrade the performance of control loops resulting in poor product quality. Therefore, plant-wide oscillation diagnosis is an essential task to maintain the performance of control loops. In recent years, significant research has been performed on plant-wide oscillation diagnosis. It has been reported that the three major causes for oscillations in linear closed-loop Single-Input Single-Output (SISO) systems are: ( i ) aggressively tuned controller, ( ii ) stiction in control valves and, ( iii ) external disturbances. Several offline data-driven methods have been developed to address the diagnosis problem by focusing on only one of the causes for oscillations. In the current study, an offline data driven approach is developed to identify all the three major causes for oscillations. This approach has the following two components: ( i ) parametric Hammerstein model based stiction detection and, ( ii ) non-parametric Hilbert-Huang spectrum analysis for distingusihing between improperly tuned controller and disturbance caused oscillations. Simulation and industrial case studies demonstrate the efficacy of the proposed method for plant-wide oscillation diagnosis. |
