An Improved Granger Causal Analysis Framework Based on Redundancy Index

The Granger causality is a very effective method for the root cause diagnosis. However, the synergy and redundancy between variables will affect the accuracy of the test result. This article introduces an unnormalized Granger causality method to detected the synergy and redundancy between variables and defined a redundancy index. Based on the index, a variable stratification method is proposed. The layered result obtained by this method can directly reflect the order in which the variables are affected by the fault. In addition, further Granger causality tests based on the layered results can make fault propagation paths more accurate. Two typical faults of the TE process were used to verify the effectiveness of the method.