At present, system-level fault detection and diagnosis (FDD) research often uses correlation-based machine learning methods combined with multiple heterogeneous diagnosis methods to improve the fault detection rate (FDR), that is, decision-level fusion. Since it does not take into account the causal direction of the decision relationship, it will affect the realization of the fusion objectives, and lead to the reduction of the fusion range and the decrease of the global decision on FDR. In this regard, the structural causal model (SCM), a commonly used causal model in causal science, can use t...
