Domain knowledge acquisition is essential in the AI planning. Derived rule is a representation to the domain knowledge based on logical reasoning. On the basis of the action model and derived rules analysis, this paper proposes a strategy of extracting domain knowledge for STRIPS world based on derived predicates and the algorithm GetDomainRule for the strategy. The domain rules extracted by the algorithm are used to reduce the logical deduction of derived rules, enhancing the efficiency of the planning. For any domain, the mutex properties of any domain can be obtained between predicates from the domain rules, applied in judging the inconsistent planning state. Finally, the strategy proposed in this paper is embedded in the planner StepByStep and experiments are conducted to extract domain rules. Experimental results show the feasibility and validity of the algorithm GetDomainRule, and the domain rules extracted by the algorithm express the causal relations between predicates directly, providing reliable domain knowledge for determining the true values of derived predicates and the following planning.