A copula-based Granger causality analysis method for root cause diagnosis of plant-wide oscillation

Abstract

In some large-scale industrial production processes, when a fault occurs in a unit, it will spread through the connectivity between the units, which can affect the entire factory and cause product quality deterioration or even more serious problems. It is important to diagnose and isolate the root cause. Granger causality analysis is widely used which provides an effective way to localize root cause of faults. However, the conventional Granger causality is not suitable for nonlinear and high-order signals. This paper proposes an effective model-free, copula-based Granger causality method for root cause diagnosis of plant-wide oscillation which can effectively reveal the nonlinear and high-order causality. Granger causality is transformed into log likelihood ratio of conditional distribution and conditional copula is used to derive an effective estimation. The numerical simulation case prove the validity of Granger causality analysis based on copula function. At the same time, for the root cause diagnosis of the actual plant-wide oscillation, this method also successfully detected the correct root cause.