Causality analysis for root cause diagnosis in Fluid Catalytic Cracking unit

PCA based monitoring have good fault detection capability, however it can only point to few variables that have contribution in occurrence of fault and it cannot recognize the main root. Since there is cause and effect relationship between different variables in a process, accordingly a network based on transfer entropy methods was constructed for each case to show causal effect between different variables and to see propagation path of fault. It was shown that PCA in combination with causality analysis based on network construction is a powerful tool for diagnosing the root cause of a fault in the process. In this paper the proposed methodology was applied to Fluid Catalytic Cracking unit as a case study.