For there are all kinds of faults in the power system, and the condition of the circuit breaker tripped and caused widespread power outages, this paper proposes a modeling  simple  optimization of multisource information fusion of intelligent fault diagnosis methods.Through analyzing the cause of the power system transmission line fault, determined based on the genetic algorithm (GA) of the fault diagnosis rules.Using rough set (RS) theory, the RS to the maximum fault decision table is reduced, this method preserves the key information obtained the minimum expression of knowledge at the same time, to be able to more quickly and accurately diagnose the fault location.Experiments proved that the proposed fault diagnosis model is efficient, for the diagnosis of power line fault provides an effective method.Through analyzing the cause of the power system transmission line fault, the fault diagnosis rules based on genetic algorithm is determined.Using rough set theory to the maximum fault decision table is reduced, this method preserves the key information obtained the minimum expression of knowledge at the same time, to be able to more quickly and accurately diagnose the fault location.Experiments proved that the proposed fault diagnosis model is efficient and can be applied to fault diagnosis of large power system, especially for transmission line fault diagnosis, the diagnosis of power line fault provides a practical and effective method.