Dynamic Bayesian Approach for Control Loop Diagnosis with Underlying Mode Dependency

作者：Qi Fei; Huang Biao^*

来源：Industrial & Engineering Chemistry Research, 2010, 49(18): 8613-8623.

DOI：10.1021/ie100058y

In this article, first, a hidden Markov model is built to address the temporal mode dependency problem in control loop diagnosis. A data-driven algorithm is developed to estimate the mode transition probability. The new solution to mode dependency is then further synthesized with the solution to evidence dependency to develop a recursive autoregressive hidden Markov model for online control loop diagnosis. When both the mode and evidence transition information sets are considered, the temporal information is effectively synthesized under the Bayesian framework. A simulated distillation column example and a pilot-scale experiment example are investigated to demonstrate the ability of the proposed diagnosis approach.

• 出版日期2010-9-15