关键词: 模糊模型，离子群优化算法，神经网络，故障诊断

Abstract: To solve fuzzy and non-linear features of faults,a fault diagnosis method was developed based on extended T-S ( Takagi- Sugeno) fuzzy model of self-adaptive disturbed PSO (Particle Swarm Optimization) combined with Neural Network. Firstly, the membership function of the basic T-S fuzzy model was modified by the adaptive gaussian function,and then the extended T-S model was used to adjust the PSO parameter. Secondly, the neural network was trained by the modified PSO algorithm. Finally, the proposed method in the paper was applied to fault diagnosis of gear-box The diagnosis results show that the mean sctuare error is improved 0.1981% , meanwhile, comparisons with the diagnosis result of the different models show the method in the paper is convenient, efficient, and provides a new approach to fault diagnosis.

Key words: Fuzzy model, Particle swarm optimization, Neural network, Fault diagnosis