关键词: 微粒群算法，遗传算法，BP神经网络，粗糙集理论，故障诊断

Abstract: For the imperfections of BP network fault diagnosis model, including the complexity of the network structure, the long time of training, and the low precision, this article introduced rough set(RS) , particle swarm optimization(PSO) and genetic algorithm(GA) into the diesel engine fault diagnosis, then proposed a new algorithm that is based on rough set theory and the improved 13P neural network. hhe algorithm uses self-organization mapping net(SOM) to discretize the continuous attributes, rough set theory to make a reduction on the properties for characteristic parameters,and the particle swarm optimization(PSO) to optimize the BP network structure,so that it can shorten training time and improve the accuracy of fault diagnosis effectively. Finally, the result of the diesel engine's diagnosis proves the fcasibilily, rapidity, veracity of the algorithm.

Key words: Particle swarm optimization(PSO) , Genetic algorithm(GA) ,BP neural network, Rough set(RS) , Fault diagnosis