Abstract: Existing fault location algorithms cannot be effectively applied in complex systems with load balancing mechanisms in which causality changes frequently. To this end, a fault location algorithm based on causal rules (CRFLA) is proposed. Firstly, the causal rules between faults and events are adaptively learned by the improved causal association interesting measure method, then the root cause is inferred according to the influence degree of the fault cause set on the occurred event set. The method considers causality without the need to specify a specific causal network structure, and can flexibly combine prior knowledge. Using the data generated by the real production environment in the power marketing system to locate the fault, the experiment results show that CRFLA is superior to the traditional method, and can quickly and effectively locate the root cause.

Key words: fault location, causal rules, load balancing, electric power marketing system