关键词: 故障诊断, 神经网络, 粗糙集, 属性约简

Abstract: This paper introduces rough sets theory.And rough sets theory is used to eliminate unnecessary attributes from the decision table.Then make improvement BP network as the back processor of rough set，and a fault diagnosis model based on rough set and neural network.The result of emluator indicats that this method can reduce the needed training samples and simply the neural network structure and shortened the training time of the network.It is estimated that the optimized strategy may be further applied in fault diagnoses.

Key words: fault diagnosis, neural network, rough set, attribute reduction